Relevant bibliographies by topics / HSV color models

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  2. Dissertations / Theses
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Academic literature on the topic 'HSV color models'

Author: Grafiati
Published: 4 June 2025
Last updated: 6 July 2025

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Journal articles on the topic "HSV color models"

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Rasid Mamat, Abd, Fatma Susilawati Mohamed, Mohamad Afendee Mohamed, Norkhairani Mohd Rawi, and Mohd Isa Awang. "Silhouette index for determining optimal k-means clustering on images in different color models." International Journal of Engineering & Technology 7, no. 2.14 (2018): 105. http://dx.doi.org/10.14419/ijet.v7i2.14.11464.

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Clustering process is an essential part of the image processing. Its aim to group the data according to having the same attributes or similarities of the images. Consequently, determining the number of the optimum clusters or the best (well-clustered) for the image in different color models is very crucial. This is because the cluster validation is fundamental in the process of clustering and it reflects the split between clusters. In this study, the k-means algorithm was used on three colors model: CIE Lab, RGB and HSV and the clustering process made up to k clusters. Next, the Silhouette Index (SI) is used to the cluster validation process, and this value is range between 0 to 1 and the greater value of SI illustrates the best of cluster separation. The results from several experiments show that the best cluster separation occurs when k=2 and the value of average SI is inversely proportional to the number of k cluster for all color model. The result shows in HSV color model the average SI decreased 14.11% from k = 2 to k = 8, 11.1% in HSV color model and 16.7% in CIE Lab color model. Comparisons are also made for the three color models and generally the best cluster separation is found within HSV, followed by the RGB and CIE Lab color models.
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Hema, D., and Dr S. Kannan. "Interactive Color Image Segmentation using HSV Color Space." Science & Technology Journal 7, no. 1 (2019): 37–41. http://dx.doi.org/10.22232/stj.2019.07.01.05.

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The primary goal of this research work is to extract only the essential foreground fragments of a color image through segmentation. This technique serves as the foundation for implementing object detection algorithms. The color image can be segmented better in HSV color space model than other color models. An interactive GUI tool is developed in Python and implemented to extract only the foreground from an image by adjusting the values for H (Hue), S (Saturation) and V (Value). The input is an RGB image and the output will be a segmented color image.
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Haouassi, Samia, and Di Wu. "An Efficient Attentional Image Dehazing Deep Network Using Two Color Space (ADMC2-net)." Sensors 24, no. 2 (2024): 687. http://dx.doi.org/10.3390/s24020687.

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Image dehazing has become a crucial prerequisite for most outdoor computer applications. The majority of existing dehazing models can achieve the haze removal problem. However, they fail to preserve colors and fine details. Addressing this problem, we introduce a novel high-performing attention-based dehazing model (ADMC2-net)that successfully incorporates both RGB and HSV color spaces to maintain color properties. This model consists of two parallel densely connected sub-models (RGB and HSV) followed by a new efficient attention module. This attention module comprises pixel-attention and channel-attention mechanisms to get more haze-relevant features. Experimental results analyses can validate that our proposed model (ADMC2-net) can achieve superior results on synthetic and real-world datasets and outperform most of state-of-the-art methods.
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Sharma, Bhubneshwar, and Rupali Nayyer. "Use and analysis of color models in image processing." International Journal of Advances in Scientific Research 1, no. 8 (2015): 329. http://dx.doi.org/10.7439/ijasr.v1i8.2460.

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The use of color image processing is divided by two factors. First color is used in object identification and simplify extraction from a scene and color is powerful descriptor.Second, humans can used thousands of color shades and intensities.Color Image Processing is divided into two areas full color and pseudocolor processing.In this processing various color models are used that are based on color recognition,color components etc. A few papers on various applications such as lane detection, face detection, fruit quality evaluation etc based on these color models have been published. A survey on widely used models RGB,HSI, HSV, RGI etc is represented in this paper.
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SEDYKH, I. A., and A. E. KHARITONOV. "ANALYSIS OF MAIN COLOR MODELS FOR IMAGE SUPER RESOLUTION." Vestnik LSTU, no. 2 (2024): 36–45. http://dx.doi.org/10.53015/23049235_2024_2_36.

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The article discusses the effectiveness of the RGB, HSV, HSL, YCbCr, Lab color models for image super resolution, considers the research procedure using metrics, presents the research results as a table and concludes about the work done.
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Nurbaity, Sabri, Ibrahim Zaidah, and Isa Dino. "Evaluation of Color Models for Palm Oil Fresh Fruit Bunch Ripeness Classification." Indonesian Journal of Electrical Engineering and Computer Science 11, no. 2 (2018): 549–57. https://doi.org/10.11591/ijeecs.v11.i2.pp549-557.

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This paper investigates the application of eight color models for automatic palm oil Fresh Fruit Bunch (FFB) ripeness classification with multi-class Support Vector Machine (SVM). Ripeness classification is important during harvesting to ensure that they are harvested during the correct ripe stage for optimum oil production. Since color is a significant indicator for agriculturists to determine the ripeness of FFB, it is critical to determine the right color model. Eight color models have been investigated namely, HSV, I1I2I3, LAB, XYZ, YCbCr, YIQ, YUV and RGB. Color moments were extracted from each of these color models for the classification of four stages of FFB ripeness that are unripe, under-ripe, ripe and over-ripe. A database of five hundred images of palm oil FFB has been constructed and experiments showed that YCbCr and YUV outperform the other color models.
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Li, Zhiyong, Pengfei Li, Xiaoping Yu, and Mervat Hashem. "Real-Time Tracking by Double Templates Matching Based on Timed Motion History Image with HSV Feature." Scientific World Journal 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/793769.

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It is a challenge to represent the target appearance model for moving object tracking under complex environment. This study presents a novel method with appearance model described by double templates based on timed motion history image with HSV color histogram feature (tMHI-HSV). The main components include offline template and online template initialization, tMHI-HSV-based candidate patches feature histograms calculation, double templates matching (DTM) for object location, and templates updating. Firstly, we initialize the target object region and calculate its HSV color histogram feature as offline template and online template. Secondly, the tMHI-HSV is used to segment the motion region and calculate these candidate object patches’ color histograms to represent their appearance models. Finally, we utilize the DTM method to trace the target and update the offline template and online template real-timely. The experimental results show that the proposed method can efficiently handle the scale variation and pose change of the rigid and nonrigid objects, even in illumination change and occlusion visual environment.
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Garashchenko, Yaroslav, Vladimir Fedorovich, Andrii Poharskyi, Olena Harashchenko, and Andrii Malyniak. "COLOR VISUALIZATION OF 3D-MODELS FOR ENHANCED PREPARATION OF ADDITIVE MANUFACTURING PROCESSES." Cutting & Tools in Technological System, no. 101 (December 7, 2024): 77–85. https://doi.org/10.20998/2078-7405.2024.101.07.

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The main aspects of color visualization of triangulated models of industrial products are presented. The implementation of visualization capabilities is based on RGB and HSV color models. The structure and key features of the software implementation of color visualization and the export of the displayed image in PLY, and AMF formats are discussed. Methods for transformations between RGB and HSV color models are described, as well as an algorithm for coloring the triangular faces of the model based on specified color ranges. The developed algorithms allow for a sufficiently informative representation of the desired areas of the product's surfaces by significantly altering one color component while minimally changing the other two. This is achieved by directing the assignment of functional dependencies and value ranges for each component of the color model. Examples of various methods for color shading of vertices and/or edges and/or faces of the model are provided. The visualization subsystem enables the analysis of the geometric characteristics of the polygonal model during the preparation phase of additive manufacturing processes. Significant advantages of these approaches to color visualization are evident when adapting the product design to technological requirements (design preparation) and when solving optimization tasks in technological preparation. The developed software is integrated into the technological preparation system for manufacturing enterprises in the machine engineering sector. This research was developed at the Department of "Integrated Technologies of Mechanical Engineering" named after M. Semko of NTU "KhPI".
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Qasim Mohammed Hussein, Ahmed Saadi Abdullah, and Nada Qasim Mohammed. "The efficiency of Color Models layers at Color Images as Cover in text hiding." Tikrit Journal of Pure Science 21, no. 1 (2023): 130–39. http://dx.doi.org/10.25130/tjps.v21i1.963.

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The color images are used widely as a cover in hiding of the information. Since the variety of applications of the color image there are several color models of color image. Most color models consist of three layers. The nature of the color mode of the cover plays a main role in determining the robustness and security of hiding algorithm.
 The objective of this paper tests the layers, components, of the color models of cover color images, to figure out which color layer of each color model is best (less affected) to use as a cover to hide information within each color model in the hiding process. The experiments concentrate on the hiding texts in two positions of each layer, 7th bits and 8th bits (LSB). Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR) were used to measure the affected of hidden text in layers. The tests were done on nine colors models: RGB, HSV, HIS, HSL, HSB, YCbCr, La*b*, LUV and CMYK.
 The results show that some of color models have best layer to hide text such as YCbCr, HSI, CMYK, HSL and LUV . In other color models which have been tested, there is not a distinctive layer. The layer H is the worst because any hiding leaves a clear impact on the cover image.
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Park, So-Yeon, Jin Ho Kim, Ji Hyun Chang, Jong Min Park, Chang Heon Choi, and Jung-In Kim. "Quantitative evaluation of radiodermatitis following whole-breast radiotherapy with various color space models: A feasibility study." PLOS ONE 17, no. 3 (2022): e0264925. http://dx.doi.org/10.1371/journal.pone.0264925.

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Purpose We analyzed skin images with various color space models to objectively assess radiodermatitis severity in patients receiving whole-breast radiotherapy. Methods Twenty female patients diagnosed with breast cancer were enrolled prospectively. All patients received whole-breast radiotherapy without boost irradiation. Skin images for both irradiated and unirradiated breasts were recorded in red-green-blue (RGB) color space using a mobile skin analysis device. For longitudinal analysis, the images were acquired before radiotherapy (RTbefore), approximately 7 days after the first fraction of radiotherapy (RT7days), RT14days, and approximately 10 days after radiotherapy completion (RTafter). Four color space models (RGB, hue-saturation-value (HSV), L*a*b*, and YCbCr models) were employed to calculate twelve color space parameters for each skin image. Skin dose measurements for irradiated breasts were performed using nanoDot optically stimulated luminescent dosimeters on the first fraction of radiotherapy. Subsequently, acute radiation dermatitis in each patient was assessed according to the Radiation Therapy Oncology Group scoring criteria at both RT14days and RTafter. Finally, several statistical analysis methods were applied to investigate the performance of the color space parameters to objectively assess the radiodermatitis. Results Owing to radiation-induced skin damage, R value of RGB model as well as S and V values of the HSV model for irradiated breasts increased significantly, while those for unirradiated breasts showed smaller increases. These parameters showed the longitudinal changes in color space parameters within each group and between groups over time with statistical significance. Strong correlations of the parameters for irradiated breasts at RT7days with skin doses and those at RTafter were observed with statistical significance. Conclusion The R value of RGB model as well as the S and V values of HSV model showed relatively better performance in evaluating the acute radiation dermatitis. These color space parameters could therefore serve as useful tools to assess radiodermatitis severity in a dose-dependent manner.
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Dissertations / Theses on the topic "HSV color models"

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Shayeghpour, Omid. "Improving information perception from digital images for users with dichromatic color vision." Thesis, Linköpings universitet, Institutionen för teknik och naturvetenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-101984.

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Color vision deficiency (CVD) is the inability or limited ability to recognize colors and discriminate between them. A person with this condition perceives a narrower range of colors compared to a person with a normal color vision. A growing number of researchers are striving to improve the quality of life for CVD patients. Finding cure, making rectification equipment, providing simulation tools and applying color transformation methods are among the efforts being made by researchers in this field. In this study we concentrate on recoloring digital images in such a way that users with CVD, especially dichromats, perceive more details from the recolored images compared to the original image. The main focus is to give the CVD user a chance to find information within the picture which they could not perceive before. However, this transformed image might look strange or unnatural to users with normal color vision. During this color transformation process, the goal is to keep the overall contrast of the image constant while adjusting the colors that might cause confusion for the CVD user. First, each pixel in the RGB-image is converted to HSV color space in order to be able to control hue, saturation and intensity for each pixel and then safe and problematic hue ranges need to be found. The method for recognizing these ranges was inspired by a condition called “unilateral dichromacy” in which the patient has normal color vision in one eye and dichromacy in another. A special grid-like color card is designed, having constant saturation and intensity over the entire image, while the hue smoothly changes from one block to another to cover the entire hue range. The next step is to simulate the way this color card is perceived by a dichromatic user and finally to find the colors that are perceived identically from two images and the ones that differ too much. This part makes our method highly customizable and we can apply it to other types of CVD, even personalize it for the color vision of a specific observer. The resulting problematic colors need to be dealt with by shifting the hue or saturation based on some pre-defined rules. The results for the method have been evaluated both objectively and subjectively. First, we simulated a set of images as they would be perceived by a dichromat and compared them with simulated view of our transformed images. The results clearly show that our recolored images can eliminate a lot of confusion from user and convey more details. Moreover, an online questionnaire was created and 39 users with CVD confirmed that the transformed images allow them to perceive more information compared to the original images.
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Šimunský, Martin. "Vliv barevných modelů na chování konvolučních neuronových sítí." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2020. http://www.nusl.cz/ntk/nusl-416630.

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Current knowledge about impact of colour models on performance of convolutional neural network is investigated in the first part of this thesis. The experiment based on obtained knowledge is conducted in the second part. Six colour models HSV, CIE 1931 XYZ, CIE 1976 L*a*b*, YIQ a YCbCr and deep convolutional neural network ResNet-101 are used. RGB colour model achieved the highest classification accuracy, whereas HSV color model has the lowest accuracy in this experiment.
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Zámečník, Dušan. "Rozpoznání dopravních značek využitím neuronové sítě." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2009. http://www.nusl.cz/ntk/nusl-217876.

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This paper deals with traffic signs recognition. Red color area is obtained by thresholding in HSV color model. Selected radiometric deskriptors, Hough transform deskriptors and neural networs are used to classification. In conclusion has been designed complex decision algorithm.
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Oliveira, Helton Jader Souza de. "Desenvolvimento de um espectrofotômetro para medidas de absorção/emissão na região do visível utilizando mini lâmpada incandescente, mídia de DVD e smartphone." Universidade Federal da Paraíba, 2015. http://tede.biblioteca.ufpb.br:8080/handle/tede/8187.

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Submitted by Maike Costa (maiksebas@gmail.com) on 2016-05-10T13:37:38Z No. of bitstreams: 1 arquivo total.pdf: 3109388 bytes, checksum: 647810f9fb25d144a271d5f256240096 (MD5)<br>Made available in DSpace on 2016-05-10T13:37:38Z (GMT). No. of bitstreams: 1 arquivo total.pdf: 3109388 bytes, checksum: 647810f9fb25d144a271d5f256240096 (MD5) Previous issue date: 2015-08-27<br>Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES<br>A spectrophotometer for absorption measurements / emission, simple, portable and as partially partial dual mode for quantitative experiments was constructed using cheap and available materials is proposed in this paper. The instrument, here called SpectroPhone consists of modules made of MDF, one DVD as a diffraction grating media, two mini white incandescent lamps as radiation source and a Smartphone to acquire images and perform data processing, such as detector. The pixels of a region produced in a spectral images provide qualitative and quantitative information after the application of the concepts and HSV color model RGB, respectively. A simple algorithm based on HSV was developed for the conversion of the hue values (H) in their corresponding λ. Its analytical performance was assessed by quantitative analysis based on analytical curves, specimens of which have been validated by analysis of variance (ANOVA). The SpectroPhone was applied to the determination of Fe2+ in the absorption mode in pharmaceutical samples, and Na+, in emission mode and in natural saline water. For comparison purposes, a commercial spectrophotometer for absorption mode and a photometer for commercial flame emission mode were used to construct the calibration curves of the reference instrument. Applying the paired t test at 95% confidence for the results of concentrations obtained with the instruments, it is observed that there was no statistically significant difference showing high precision and accuracy. SpectroPhone can be considered a good alternative to instrumental spectrometric measurements, not just limited to educational and academic purposes.<br>Um espectrofotômetro para medidas de absorção/emissão, simples, parciamente portátil e modo duplo parcial para experimentos quantitativos foi construído usando materiais baratos e disponíveis é proposto neste trabalho. O instrumento, aqui chamado de SpectroPhone é composto por módulos confeccionados em MDF, uma mídia de DVD como rede de difração, duas mini lâmpadas incadescentes branca como fonte de radiação e um Smartphone para adquirir imagens e realizar tratamento de dados, como detector. Os pixels de uma região produzida em uma imagens digital fornecem informações qualitativas e quantitativas após a aplicações do HSV e conceitos do modelo de cor RGB, respectivamente. Um simples algoritmo baseado em HSV foi desenvolvido para a conversão dos valores do matiz (H) em seu λ correspondentes. Seu desempenho analítico foi avaliado por meio de análises quantitativas baseados em curvas analíticas, cujos modelos foram validados por meio da análise de variância (ANOVA). O SpectroPhone foi aplicado na determinação de Fe2+ no modo de absorção em amostras farmacêuticas, e Na+, no modo de emissão em soro fisiológico e em água naturais. Para fins de comparação, um espectrofotômetro comercial para o modo de absorção e um fotômetro em chama comercial para o modo de emissão foram empregados para construir as curvas analíticas do instrumento de referência. Aplicando o teste t pareado ao nível de 95% de confiança para os resultados de concentrações obtidas com os instrumentos, observa-se que não houve diferença estatisticamente significativa apresentando alta precisão e exatidão. O SpectroPhone pode ser considerado uma boa alternativa instrumental para medições espectrométricas, não apenas limitada para fins didáticos e acadêmicos.
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Feitosa, Rafael Divino Ferreira. "Modelos matemáticos para redução do espectro provável e detecção de tons de pele humana em imagens coloridas representadas nos espaços de cores RGB e HSV." Universidade Federal de Goiás, 2015. http://repositorio.bc.ufg.br/tede/handle/tede/4756.

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Submitted by Erika Demachki (erikademachki@gmail.com) on 2015-10-23T18:23:32Z No. of bitstreams: 2 Dissertação - Rafael Divino Ferreira Feitosa - 2015.pdf: 7893703 bytes, checksum: 12af470c3ca2fb4a3d0bd3885bfde46d (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5)<br>Approved for entry into archive by Erika Demachki (erikademachki@gmail.com) on 2015-10-23T18:25:45Z (GMT) No. of bitstreams: 2 Dissertação - Rafael Divino Ferreira Feitosa - 2015.pdf: 7893703 bytes, checksum: 12af470c3ca2fb4a3d0bd3885bfde46d (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5)<br>Made available in DSpace on 2015-10-23T18:25:45Z (GMT). No. of bitstreams: 2 Dissertação - Rafael Divino Ferreira Feitosa - 2015.pdf: 7893703 bytes, checksum: 12af470c3ca2fb4a3d0bd3885bfde46d (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Previous issue date: 2015-04-14<br>Skin detection techniques are widely applied to locate and to track parts of the human body with the objective of posterior recognition, having received great attention in recent years in the development of research in reason to the innumerable possible applications with the detection and tracking of faces, identification of naked people, identification of hand movements, among others. The present work proposed the construction of mathematical models for the detection of human skin tones such as, white, yellow, brown and black in digital color images in the RGB and HSV color spaces. Using a set of human skin tone samples, mathematical models were constructed describing how the variables of each color pixel in the RGB and HSV systems interrelate. To understand the answer of the proposed system, the mechanistic model was chosen, dividing it into components, observing the behavior of each part and the interactions that occurred between them. The proposed RGB filter reached a 98.3657% reduction index of the spectrum, classifying only 1.6343% (253,159 tones) as possible skin tones and the HSV model reduced the likely spectrum to 2.5352% (94,030 tones), discarding 97.4648% of the colors as candidates for human skin tones. When the proposed filters, were applied to the reduction of the probable range of human skin tones, well-defined bands in the geometric representation of the color spaces were selected. The experimental validation of the effectiveness of the RGB model showed that the proposed filter has conservative characteristics in the detection of skin, mistakenly classifying as skin only 6.7163% of the sample space. The proposed RGB filter has low sensitivity of 61.0831% and high specificity of 95.2769% in the detection of human skin in digital images. The HSV model had rates of (54,6333%) low sensitivity and (92,6390%) high specificity, considered low when compared to the performance of the other algorithms.<br>Técnicas de detecção de pele são amplamente aplicadas para localizar e rastrear partes do corpo humano com o objetivo de posterior reconhecimento, tendo recebido nos últimos anos grande atenção no desenvolvimento de pesquisas em razão das inúmeras aplicações possíveis como detecção e rastreamento de faces, identificação de pessoas nuas, identificação de movimentos das mãos, entre outras. O presente trabalho propôs construir 2 modelos matemáticos para detecção de tons de pele humana branca, amarela, parda e preta em imagens digitais coloridas nos espaços de cores RGB e HSV. Utilizandose de um conjunto de amostras de tons de pele humana foram construídos modelos matemáticos que descrevem como as variáveis de cada pixel de cor nos sistemas RGB e HSV se relacionam. Para compreender a resposta do sistema proposto, foi escolhido o modelo mecanístico, dividindo-o em componentes e observando o comportamento de cada parte e das interações que ocorreram entre elas. O filtro RGB proposto alcançou o índice de redução de 98,3657% do espectro, classificando apenas 1,6343% (253.159 tons) como possíveis tons de pele e o modelo HSV reduziu para 2,5352% (94.030 tons) o espectro provável, descartando 97,4648% das cores como candidatas a tons de pele humana. Os filtros propostos, quando aplicados à redução do espectro provável de tons de pele humana, selecionaram faixas bem definidas na representação geométrica dos espaços de cores. A validação experimental da eficácia do modelo RGB mostrou que o filtro proposto apresenta características conservadoras na detecção de pele classificando como pele, erroneamente, apenas 4,5075% do espaço amostral. O filtro RGB proposto possui baixa sensibilidade de 56,9698% e elevada especificidade de 95,4925% na detecção de pele humana em imagens digitais. O modelo HSV apresentou taxas de baixa sensibilidade (54,6333%) e alta especificidade (92,6390%), quando comparadas ao desempenho dos demais algoritmos propostos na literatura.
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Memarzadeh, Milad. "Automated 2D Detection and Localization of Construction Resources in Support of Automated Performance Assessment of Construction Operations." Thesis, Virginia Tech, 2012. http://hdl.handle.net/10919/76908.

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This study presents two computer vision based algorithms for automated 2D detection of construction workers and equipment from site video streams. The state-of-the-art research proposes semi-automated detection methods for tracking of construction workers and equipment. Considering the number of active equipment and workers on jobsites and their frequency of appearance in a camera's field of view, application of semi-automated techniques can be time-consuming. To address this limitation, two new algorithms based on Histograms of Oriented Gradients and Colors (HOG+C), 1) HOG+C sliding detection window technique, and 2) HOG+C deformable part-based model are proposed and their performance are compared to the state-of-the-art algorithm in computer vision community. Furthermore, a new comprehensive benchmark dataset containing over 8,000 annotated video frames including equipment and workers from different construction projects is introduced. This dataset contains a large range of pose, scale, background, illumination, and occlusion variation. The preliminary results with average performance accuracies of 100%, 92.02%, and 89.69% for workers, excavators, and dump trucks respectively, indicate the applicability of the proposed methods for automated activity analysis of workers and equipment from single video cameras. Unlike other state-of-the-art algorithms in automated resource tracking, these methods particularly detects idle resources and does not need manual or semi-automated initialization of the resource locations in 2D video frames.<br>Master of Science
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Alsafi, Radi Taha M. "Generation of complex recombinant fowlpox virus 9 (FP9) encoding simian immunodeficiency virus (SIVmac239) sequences as a model HIV vaccine candidate." Thesis, University of Manchester, 2016. https://www.research.manchester.ac.uk/portal/en/theses/generation-of-complex-recombinant-fowlpox-virus-9-fp9-encoding-simian-immunodeficiency-virus-sivmac239-sequences-as-a-model-hiv-vaccine-candidate(1a015762-8dc2-4153-a586-d7fab88b9658).html.

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The development of a safe and effective HIV vaccine remains challenging due to its high antigenic variability. Poxviruses are large, stable, and have a track record of use as human vaccine candidates. Recombinant fowlpox virus 9 (rFP9), a highly attenuated host range-restricted poxvirus strain, has been safely administered to humans with no ill effects, and is known to be immunogenic. This thesis describes the construction of complex rFP9 encoding various sequences of SIVmac239. The SIVmac239/macaque model is widely used for HIV vaccine development. The ultimate aim of this work was to combine the advantages of FP9 with those of live attenuated SIV to produce a safe yet hopefully effective model HIV vaccine candidate. Transfer plasmids for five different insertion sites within the FP9 genome were designed and constructed. Homologous recombination (HR) of adjacent FP9 sequences was employed to facilitate the integration of SIVmac239 sequences into the FP9 genome. Positive rFP9 were identified by blue colouration in presence of X-gal using a transient colour selection (TCS) technique, and the final markerless pure recombinants were confirmed by PCR. Expression of the target SIV proteins in the presence of T7 polymerase has been demonstrated by immunocytochemical (ICC) staining and Western blotting (WB) assays. Expression was also quantified by enzyme-linked immunosorbent assay (ELISA) in various cell lines at multiple time points. Five different unique rFP9 have been constructed through this project. All SIVmac239 open reading frames (ORFs) save nef have been integrated into the FP9 genome, and protein expression demonstrated where possible. Moreover, a single rFP9 vector expressing the defective SIVmac239 genome driven by T7 RNA polymerase has been successfully constructed and validated using a green fluorescent protein marker.rFP9 showed appropriate transgene expression in both avian and mammalian cells, although at different levels. The expression efficiency of rFP9 was finally compared to another attenuated poxvirus vector, modified vaccinia Ankara (MVA). Comparing the protein expression levels between rFP9 and rMVA was quite difficult because different poxvirus promoters (early/late in rFP9; intermediate in rMVA) were used to direct the transcription of the T7 RNA gene. Given this limitation, although generally higher levels of expression were seen with rFP9, this cannot be attributed to the FP9 with any certainty.
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Tokatli, Aykut. "3d Hand Tracking In Video Sequences." Master's thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/12606461/index.pdf.

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The use of hand gestures provides an attractive alternative to cumbersome interface devices such as keyboard, mouse, joystick, etc. Hand tracking has a great potential as a tool for better human-computer interaction by means of communication in a more natural and articulate way. This has motivated a very active research area concerned with computer vision-based analysis and interpretation of hand gestures and hand tracking. In this study, a real-time hand tracking system is developed. Mainly, it is image-based hand tracking and based on 2D image information. For separation and identification of finger parts, coloured markers are used. In order to obtain 3D tracking, a stereo vision approach is used where third dimension is obtained by depth information. In order to see results in 3D, a 3D hand model is developed and Java 3D is used as the 3D environment. Tracking is tested on two different types of camera: a cheap USB web camera and Sony FCB-IX47AP camera, connected to the Matrox Meteor frame grabber with a standard Intel Pentium based personal computer. Coding is done by Borland C++ Builder 6.0 and Intel Image Processing and Open Source Computer Vision (OpenCV) library are used as well. For both camera types, tracking is found to be robust and efficient where hand tracking at ~8 fps could be achieved. Although the current progress is encouraging, further theoretical as well as computational advances are needed for this highly complex task of hand tracking.
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Hsu, Su-Ling, and 許素玲. "The Study of HSL Color Model Used in Error Diffusion." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/36yhsg.

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碩士<br>龍華科技大學<br>資訊管理系碩士班<br>105<br>We have come into contact with 3C products in our lives, such as computers, mobile phones and tablet etc., all matter ultimately consists of by RGB (Red, Green, Blue), but RGB which depend on the different hardware devices have variety colors, for example the same picture in the computer and notebook computer screen displays the color will be different, ordinary people do not know what is RGB, for the provision of materials manufacturers are not intuitive, and the computer spend too much computing time to display a photo. HSL(Hue, Saturation, Lightness) is closer than RGB in our lives the way people understand the color HSL. The W3C website CSS3.0 also joined this color space (Tefen et al., 2015) as a color setting in the past few years. The research will use the HSL as a color model to process the error diffusion for deducing color in a photo and compare distorted photos by error diffusion with deferent color models such as HSL and RGB. We will give the alternative option and second opinion for the color model HSL of error diffusion. We also find out that HSL as a color model applied error diffusion has a better result of execution time and same image quality with RGB.
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Lin, Kai-Sin, and 林楷欣. "HSV color model applied to the development of steel rustimage recognition system for handheld devices." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/q3wuu5.

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碩士<br>國立臺灣大學<br>土木工程學研究所<br>107<br>The research related to bridge engineering plays an important role in Taiwan&apos;&apos;s construction industry. In Taiwan, the percentage of the degree of rust is considered as the standard of repainting steel bridge. Howerer, percentage is quantitative data, which needs to be measured by professional methods instead of subjective judgment. Therefore, this study combines the concept of image recognition with the goal of designing a system, which can read photos and automatically determine the rust and calculate the proportion. After that, this research combines it with a smart portable device to produce a mobile application system. The system principle is to define the range of "corrosion" through the HSV color model and to judge and identify. At the end of this research, the output system will be compared to the system which uses edge detection algorithm, and find that good results are obtained in terms of identification efficiency and computation speed.
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Books on the topic "HSV color models"

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Gordon, Phillip. The Color Purple and the Wine-Dark Kiss of Death. University of Illinois Press, 2017. http://dx.doi.org/10.5406/illinois/9780252039805.003.0011.

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Alice Walker's 1982 novel The Color Purple was published six months after AIDS was first described in medical literature. This chapter reads The Color Purple as an AIDS narrative by looking into the surrounding details of its publication to uncover what may have been an accidental narrative for Walker as she wrote her masterpiece but that proves nonetheless as important for our current moment as the novel was, in the moment of its publication, for second-wave feminism. A close consideration of the details of the novel reveals a subnarrative with devastating relevance to the lives of black women living in the Southeastern United States in the opening decades of the twenty-first century. By considering the sexual economy, the emphasis on illness and sexual contact, the postcolonial interests (which is to say, considering Africa), and the time and place of its writing, it is argued that The Color Purple should be read as the first AIDS narrative in American literature. Such a reading is a profound revision of our current model of AIDS literature and bears implications for our current political understanding of HIV/AIDS, a disease long associated with forgotten and unwanted populations.
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Book chapters on the topic "HSV color models"

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Lawrence, Amith, N. V. Manoj Ashwin, and K. Manikantan. "Face Recognition Using Background Removal Based on Eccentricity and Area Using YCbCr and HSV Color Models." In Lecture Notes in Electrical Engineering. Springer India, 2016. http://dx.doi.org/10.1007/978-81-322-3592-7_4.

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Thanh, Le Thi, and Dang N. H. Thanh. "An Adaptive Local Thresholding Roads Segmentation Method for Satellite Aerial Images with Normalized HSV and Lab Color Models." In Intelligent Computing in Engineering. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2780-7_92.

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Ji, Shibo, and Xia Li. "HSB Color Strategy model Based on Color Cognition and Color Emotion." In Atlantis Highlights in Intelligent Systems. Atlantis Press International BV, 2023. http://dx.doi.org/10.2991/978-94-6463-266-8_22.

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Tian, Gang, Ruimin Hu, Zhongyuan Wang, and Youming Fu. "Improved Object Tracking Algorithm Based on New HSV Color Probability Model." In Advances in Neural Networks – ISNN 2009. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01510-6_130.

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Yu, Mengqi, Pengxiang Liu, Zihuan Gao, Heng Li, and Hui Peng. "Vehicle Detection Technology Based on HSV Color Model and Edge Detection." In Proceedings of International Conference on Image, Vision and Intelligent Systems 2022 (ICIVIS 2022). Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0923-0_62.

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Anwar, Shamama, Subham Kumar Sinha, Snehanshu Vivek, and Vishal Ashank. "A Vision-Based Segmentation Technique Using HSV and YCbCr Color Model." In Image Processing and Intelligent Computing Systems. CRC Press, 2022. http://dx.doi.org/10.1201/9781003267782-14.

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Kang, Bing, Fu Liu, and Shoukun Jiang. "The Identification to the Palm Color Spots Based on Improved HSV Model." In Geo-Informatics in Resource Management and Sustainable Ecosystem. Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-49155-3_65.

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Yao, Lei, Deng Xiaolu, and Wang Yufeng. "Soccer Robots’ Color Logos Recognition Based on HSI Model and Eigenvalues." In Electrical, Information Engineering and Mechatronics 2011. Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2467-2_81.

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Tran, Trung-Thien, Chan-Su Bae, Young-Nam Kim, Hyo-Moon Cho, and Sang-Bock Cho. "An Adaptive Method for Lane Marking Detection Based on HSI Color Model." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14831-6_41.

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Dai, Yikang, Chengqi Xue, and Qi Guo. "A Study for Correlation Identification in Human-Computer Interface Based on HSB Color Model." In Human Interface and the Management of Information. Interaction, Visualization, and Analytics. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-92043-6_40.

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Conference papers on the topic "HSV color models"

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Momber, Andreas W. "Color-Based Assessment of Flash Rust." In Paint and Coatings Expo (PACE) 2010. SSPC, 2010. https://doi.org/10.5006/s2010-00034.

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Abstract The presentation reviews the utilization of color analyses for the assessment and rating of rust, whereas particular attention is spent to flash rusting. The background of flash rust formation is discussed first, along with a brief review about the composition of flash rust. The fundamentals of the HSV color model, which is selected as a simple suitable model, are introduced. Finally, the author discusses the utilization of the suggested approach for the evaluation of steel substrate cleanliness and flash rust assessment.
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Kumar, Ravi, Manikant Kumar, Shweta Kumari, Ashish Kumar, Mithilesh Kumar Rai, and Vishal Mourya. "Underwater Image Enhancement using CLAHE Fusion in YIQ and HSI Color Model." In 2024 4th International Conference on Emerging Frontiers in Electrical and Electronic Technologies (ICEFEET). IEEE, 2024. https://doi.org/10.1109/icefeet64463.2024.10865814.

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Charoensawan, Piyapat, Sukanya Phongsuphap, and Ikuko Shimizu. "Comparison of Fabric Color Naming Using RGB and HSV Color Models." In 2018 15th International Joint Conference on Computer Science and Software Engineering (JCSSE). IEEE, 2018. http://dx.doi.org/10.1109/jcsse.2018.8457329.

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Saravanan, G., G. Yamuna, and S. Nandhini. "Real time implementation of RGB to HSV/HSI/HSL and its reverse color space models." In 2016 International Conference on Communication and Signal Processing (ICCSP). IEEE, 2016. http://dx.doi.org/10.1109/iccsp.2016.7754179.

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Kolkur, S., D. Kalbande, P. Shimpi, C. Bapat, and J. Jatakia. "Human Skin Detection Using RGB, HSV and YCbCr Color Models." In International Conference on Communication and Signal Processing 2016 (ICCASP 2016). Atlantis Press, 2017. http://dx.doi.org/10.2991/iccasp-16.2017.51.

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Zui Zhang, Hatice Gunes, and Massimo Piccardi. "An accurate algorithm for head detection based on XYZ and HSV hair and skin color models." In 2008 15th IEEE International Conference on Image Processing. IEEE, 2008. http://dx.doi.org/10.1109/icip.2008.4712087.

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Abdel-Hamid, Lamiaa. "Glaucoma detection using statistical features: comparative study in RGB, HSV and CIEL*a*b* color models." In Tenth International Conference on Graphics and Image Processing (ICGIP 2018), edited by Hui Yu, Yifei Pu, Chunming Li, and Zhigeng Pan. SPIE, 2019. http://dx.doi.org/10.1117/12.2524215.

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AKO, Joel E., Camille E. N’ZI, and Kidiyo KPALMA. "Cocoa beans moisture content prediction using Machine Learning Model based on the color image features." In Computer Science Research Notes. University of West Bohemia, Czech Republic, 2024. http://dx.doi.org/10.24132/csrn.3401.25.

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The aim of this article is to investigate the possibility of modeling the moisture content of cocoa beans as a function of RGB images features of unshelled cocoa beans. Features are extracted by calculating mean, standard deviation, energy, entropy, kurtosis and skewness of the components of the rgb (RGB normalized), HSV, L*a*b*, YCbCr color spaces without the brightness components. These features are extracted from 4 types of samples, namely 10, 30, 50 and 70 bean samples per image. Feature analysis using the F-test and RReliefF methods shows that the features based on the energy and entropy of the components rg, yb, Cr, Cb, a*, b* and h* are fairly relevant for predicting the water content of cocoa beans. However, they are highly correlated. The selected predictors allow the analysis of linear models, such as Multiple Linear Regression (MLR), Ridge Regression (RR), PLS Regression (PLSR) and non-linear models, such as polynomial, Support Vector Regression (SVR) with RBF kernel, Decision Trees Regression (DTR). With the exception of RR and PLSR, the other models were preceded by a principal component analysis (PCA) to handle the collinearity problem. The non-linear models give good predictions, with coefficients of determination R2 ranging from 0.95 to 0.98 and RMSE from 2.31 to 4.08. The regularization and penalization method is more better for handling multi-colinearity between predictors. It is therefore possible to predict the moisture content of cocoa beans from the features of RGB images. However, the prediction of new data from the models designed is still problematic.
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Wang, Yuqi, Shengchao Li, Lei Zhou, and Haiyan Wang. "Effect of Balance and Symmetry on web aesthetic: Computational modeling and experimental investigation." In Human Systems Engineering and Design (IHSED 2021) Future Trends and Applications. AHFE International, 2021. http://dx.doi.org/10.54941/ahfe1001205.

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In order to objectively evaluate the beauty of webpage colors, balance and symmetry are selected as rating indicators, using HSV color model to quantify the evaluation through the principle of visual weight, and the main interface of the search engine is used as an example to verify the calculation model of the beauty of the color layout. In the experiment, 10 subjects evaluate the stimulus pictures, which verified the rationality of the computation model.
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Bassoult, Luis Ahindel Castellanos, Ricardo Alcantara, Arturo Perez Hernandez, Rafael Perez Vazquez, and Adela Velasquez. "Identification of Porous Systems in Complex Carbonates Using Artificial Intelligence." In Offshore Technology Conference. OTC, 2025. https://doi.org/10.4043/35513-ms.

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Abstract Reliable data is fundamental for volumetric hydrocarbon assessments and the development of optimal production scenarios. Understanding and interpreting reservoir behavior through porous system distribution reduces uncertainty in volumetric calculations, particularly for water saturation (Sw). Derived from Archie’s equation, Sw is a key reservoir quality indicator that is heavily influenced by the cementation exponent (m), which reflects pore system distribution and connectivity. This study introduces an innovative Artificial Intelligence (AI)-driven workflow that integrates geological, petrophysical, and production data to enhance the characterization and exploitation of Naturally Fractured Reservoirs (NFRs). By leveraging artificial intelligence, the workflow models heterogeneities, predicts reservoir performance, and reduces uncertainty, supporting decision-making in complex reservoir systems. Training, validation, and testing of the model with data from wells in different basins enabled a detailed probabilistic evaluation of key indicators, including porous system type (fractures and vugs), cementation exponent (m), Pore Aspect Ratio (AR), fluid type, reservoir quality, and classification. In Mexico, 80% of hydrocarbon production originates from NFRs; hence, this workflow builds on state-of-the-art algorithms developed exclusively for NFRs. When applied, it has been observed that the information provided helped to mitigate production decline in mature fields through the identification of remaining hydrocarbon zones and reducing risks in volumetric calculations. The study commenced with rigorous data collection and validation. Thin section analysis utilized advanced color segmentation in the Hue-Saturation Value (HSV) color space and geometric operators to discretize elements like vugs and fractures. Mathematical morphology operations, such as dilation and erosion, refined segmented areas and removed noise. Fractures and vugs were identified and segmented using the Hough Transform to detect linear and elliptical or circular contours, depending on their morphology. These were further refined with polynomial, elliptical, and circular functions, enabling precise geometric representations for detailed analysis. Segmented data were correlated with Mercury Injection Capillary Pressure (MICP) studies and Bayesian analysis of pore aspect ratios (AR) to validate and characterize fractures and vugs. Additionally, dynamic reservoir data were incorporated to align key properties with NFR classification, enhancing the fidelity of dynamic behavior reproduction. The workflow’s reliance on training data (Well-A), validation data, and test data (Wells B and C) ensured a robust machine learning framework. Training data optimized internal parameters for learning complex relationships, validation data refined hyperparameters and mitigated overfitting, and test data independently evaluated the model’s performance. This comprehensive approach provides a reliable, scalable methodology for NFR classification and reservoir management.
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Reports on the topic "HSV color models"

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Pirohov, Vladyslav M., Anna M. Horlo, and Iryna S. Mintii. Software development of the algorithm of adaptating of the website design for people with color-blindness. [б. в.], 2018. http://dx.doi.org/10.31812/123456789/2888.

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The purpose of the study is the program implementation of the basic algorithms of the website design adaptation for people with color perception. This article examines the implementation of the following algorithms: the conversion algorithm from the rgb color model to the lms model (there is a special algorithm precisely in the color model lms for modeling various types of color perception violations), simulation of different color blindness types in the lms-model (this is the transformation of normal values in the color model lms to values with different types of color perception violations), convert data from lms color model to rgb model, conversion from color rgb to hsl model, color filtering in hsl-model and conversion from hsl model to rgb color model.
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