Relevant bibliographies by topics / HSV color model

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

Author: Grafiati
Published: 4 June 2021
Last updated: 13 February 2022

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Journal articles on the topic "HSV color model"

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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 (April 6, 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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Cai, Zhao Quan, Wei Luo, Zhong Nan Ren, and Han Huang. "Color Recognition of Video Object Based on HSV Model." Applied Mechanics and Materials 143-144 (December 2011): 721–25. http://dx.doi.org/10.4028/www.scientific.net/amm.143-144.721.

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In the presented paper, we proposed a common color model and designed the color judgment method, which is based on the HSV model. This method will translate the RGB values of the points in video images to HSV values, and use HSV values to recognize the color. After that, software of real-time video object recognition was developed based on color features, which is also based on their search of target color identification. Besides, the system is developed by VC based on OpenCV, which has achieved the goal of real-time video motion detection and object color recognition. Finally, the experimental results indicate that the algorithm is accurate and similar to human recognition of the moving objects in videos view, which demonstrates the good performance of the target identification and color judgment.
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Hema, D., and Dr S. Kannan. "Interactive Color Image Segmentation using HSV Color Space." Science & Technology Journal 7, no. 1 (January 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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Astrianda, Nica. "Klasifikasi Kematangan Buah Tomat Dengan Variasi Model Warna Menggunakan Support Vector Machine." VOCATECH: Vocational Education and Technology Journal 1, no. 2 (April 13, 2020): 45–52. http://dx.doi.org/10.38038/vocatech.v1i2.27.

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Abstract Tomato ripeness classification has been done manually through direct visual observation. However, manual classification is highly influenced by operator subjectivity so that on certain conditions, the classification process is not consistent. The development of information technology allows the identification of the ripeness level of tomatoes based on the characteristics of color with the help of computers. In this study Tomato fruit is classified by histogram color image input obtained from the capture result. This is done by changing all the colors in the image of the RGB color model (Red, Green, Blue) into several different color models ie HSV color model (Hue, Saturation, Value), CIElab color model and YCBCR color model. The obtained color model will be used as training data using SVM (Support Vector Machine) so that the system is able to classify the ripeness of tomato fruit later. The image processing process of this research is done using matlab. After being analyzed manually using 20 data as training, 54 data as data testing got success rate classification of tomato fruit ripeness using Support Vector Machine is 100% by using CIElab color model. Keywords: Support Vector Machine; CIElab; HSV; YCbCr; Ripeness of Tomato ____________________________ Abstrak Klasifikasi kematangan tomat telah dilakukan secara manual melalui pengamatan visual langsung. Namun, klasifikasi manual sangat dipengaruhi oleh subjektivitas operator sehingga pada kondisi tertentu, proses klasifikasi tidak konsisten. Perkembangan teknologi informasi memungkinkan identifikasi tingkat kematangan tomat berdasarkan karakteristik warna dengan bantuan komputer. Dalam penelitian ini buah tomat diklasifikasikan berdasarkan input gambar berwarna histogram yang diperoleh dari hasil tangkapan. Hal ini dilakukan dengan mengubah semua warna pada gambar model warna RGB (Red, Green, Blue) menjadi beberapa model warna yang berbeda yaitu model warna HSV (Hue, Saturation, Value), model warna CIElab dan model warna YCBCR. Model warna yang diperoleh akan digunakan sebagai data pelatihan menggunakan SVM (Support Vector Machine) sehingga sistem mampu mengklasifikasikan kematangan buah tomat. Proses pengolahan citra pada penelitian ini dilakukan dengan menggunakan matlab. Setelah dianalisis secara manual menggunakan 20 data sebagai data pelatihan, 54 data sebagai data pengujian mendapatkan klasifikasi tingkat keberhasilan kematangan buah tomat menggunakan Support Vector Machine adalah 100% dengan menggunakan model warna CIElab. Kata Kunci: Support Vector Machine; CIElab; HSV; YCbCr; Kematangan Tomat. __________________________
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Rahaman, G. M. Atiqur, and Md Zahidul Islam. "Color transform analysis for microscale image segmentation to study halftone model parameters." Open Computer Science 6, no. 1 (November 2, 2016): 148–67. http://dx.doi.org/10.1515/comp-2016-0013.

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AbstractThis article presents a comprehensive study of 30 color transforms to accurately segment images of halftone prints and thus calculating the parameters of a color prediction model. The transforms are evaluated combining three metrics: the model accuracy,Otsu’s discriminant, and correlation coefficients of histograms. Hierarchical cluster analysis is applied to determine the thresholds to segment the image histogram into paper, ink and mixed area. Among the 30 different transforms discussed in this article, 21 channels are of 7 color space models (RGB, CMYK, CIELAB, HSV, YIQ, YCbCr, and XYZ) and the other 9 channels are specially designed. Notable increase in model accuracy validates the segmentation accuracy and the necessity of choosing the appropriate transform. A set of 180 halftone images of different print properties (such as paper, halftone, ink and printing technology) has been used for the evaluation. It is found that, the most appropriate transform depends on the type of primary ink, but the corresponding transforms in CMYK color space model have shown consistent performance. CMYK-C, XYZ-Y and LAB-B are the best transforms for Cyan, Magenta and Yellow ink color respectively. YIQ-I and HSV-S are good candidates if a single transform is to be chosen for all primary ink colors.
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Chae, Soohwan, and Kyungkoo Jun. "HSV Color Model based Hand Contour Detector Robust to Noise." Journal of Korea Multimedia Society 18, no. 10 (October 30, 2015): 1149–56. http://dx.doi.org/10.9717/kmms.2015.18.10.1149.

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Lv, Jingqin, and Jiangxiong Fang. "A Color Distance Model Based on Visual Recognition." Mathematical Problems in Engineering 2018 (2018): 1–7. http://dx.doi.org/10.1155/2018/4652526.

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In computer vision, Euclidean Distance is generally used to measure the color distance between two colors. And how to deal with illumination change is still an important research topic. However, our evaluation results demonstrate that Euclidean Distance does not perform well under illumination change. Since human eyes can recognize similar or irrelevant colors under illumination change, a novel color distance model based on visual recognition is proposed. First, we find that various colors are distributed complexly in color spaces. We propose to divide the HSV space into three less complex subspaces, and study their specific distance models. Then a novel hue distance is modeled based on visual recognition, and the chromatic distance model is proposed in line with our visual color distance principles. Finally, the gray distance model and the dark distance model are studied according to the natures of their subspaces, respectively. Experimental results show that the proposed model outperforms Euclidean Distance and the related methods and achieves a good distance measure against illumination change. In addition, the proposed model obtains good performance for matching patches of pedestrian images. The proposed model can be applied to image segmentation, pedestrian reidentification, visual tracking, and patch or superpixel-based tasks.
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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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Chen, Ching Yi, and Chi Chiang Ko. "Designing FIRA Medium-Sized Soccer Robot Vision System Using Particle Swarm Optimization." Applied Mechanics and Materials 764-765 (May 2015): 675–79. http://dx.doi.org/10.4028/www.scientific.net/amm.764-765.675.

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Enabling FIRA medium-sized soccer robots to recognize target objects according to color information requires that competing teams manually set the range of colors according to ambient lighting conditions prior to games. This color information is used to differentiate features of target objects, such as the ball, the goals, and the field. Constructing a color-feature model such as this is extremely time-consuming and the resulting model is unable to adapt dynamically to changes in lighting conditions. This study applied a look-up table method to execute RGB-HSV color space conversion to accelerate video processing. A particle swarm optimization (PSO) scheme was developed to detect the color-feature parameters of the target objects in the HSV color space. This enables the automatic completion of color-feature modeling and the construction of the knowledge model required by the robot for object recognition. Experiment results demonstrate that the proposed method is capable of enhancing the robustness of the robot vision system in determining changes in lighting conditions. In addition, the manpower and time required to set robot parameters prior to games were reduced significantly.
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Su, Ching Hung, Huang Sen Chiu, Jui Hung Hung, and Tsai Ming Hsieh. "Color Space Comparison between RGB and HSV Based Images Retrieval." Advanced Materials Research 989-994 (July 2014): 4123–26. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.4123.

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The visual attributes of color are suitable for human perception and computer vision. A Color space is defined as a model for representing the intensity value of color. We propose a color space comparison and analysis between RGB and HSV based images retrieval. We succeed in transferring the image retrieval problem to sequences comparison and subsequently using the color sequences comparison between the color featurs of RGB and HSV to compare and analyze the images of database.
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Dissertations / Theses on the topic "HSV color model"

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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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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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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES
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.
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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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.
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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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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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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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.
Master of Science
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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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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
國立臺灣大學
土木工程學研究所
107
The research related to bridge engineering plays an important role in Taiwan''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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Peng, Yan-Jyun, and 彭彥鈞. "Using the S Imformation of HSV Model and the Gray Level Values to Segment and Recognize the Guide-tile Areas in a Color Digital Image." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/52061211177777418606.

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碩士
中華大學
電機工程學系碩士班
102
The “barrier free environment” issue should be cared and considered by all of us. This thesis focuses on the detection of guide-tile paths which are especially important for blind people. 　　In the thesis, an image processing based system is proposed for segmenting and recognizing the guide-tile area(s) in a color digital image. First, the input image, which is a RGB model color image, is transformed to its HSV space representation, and only the S information is saved for further processing. Second, discrete wavelet transform are also used for reducing noise and smoothing edges, respectively. Third, the standard deviation, straight line detection, and rectangle detection results are the features for determination. Finally, a speech subsystem presents the guide-tile path detection result to the user. 　　Some guide-tile areas, which are usually with low contrast to the environments or with large standard deviation values, can not be segmented successfully (i.e. no region of interest is found in the second step). For those images, the proposed method calculates their gray-level images and enhances the contrast. Then, morphological operations, Laplacian operation, and watershed segmentation are used for segmenting the regions of interest. 　　For the images containing typical yellow guide-tile areas, the proposed system has a recognition rate up to 98%, and for those with low-contrast metal color guide-tile areas, the proposed method still has a recognition rate up to 95%. We wish to continuously evolve the system to be a robust and dependable system that could improve the life quality of blind people.
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Books on the topic "HSV color model"

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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 model"

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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, 1145–51. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01510-6_130.

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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, 620–28. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-49155-3_65.

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Musiał, Adam. "Adaptive Heuristic Colorful Text Image Segmentation Using Soft Computing, Enhanced Density-Based Scan Algorithm and HSV Color Model." In Advances in Intelligent Systems and Computing, 157–67. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-10383-9_15.

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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, 689–96. London: 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, 304–11. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14831-6_41.

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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, 33–43. New Delhi: Springer India, 2016. http://dx.doi.org/10.1007/978-81-322-3592-7_4.

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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, 477–89. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-92043-6_40.

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Deb, Kaushik, Heechul Lim, Suk-Ju Kang, and Kang-Hyun Jo. "An Efficient Method of Vehicle License Plate Detection Based on HSI Color Model and Histogram." In Next-Generation Applied Intelligence, 66–75. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02568-6_7.

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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, 865–72. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2780-7_92.

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Li, Dongchen, Shengyong Xu, Yuezhi Zheng, Changgui Qi, and Pengjiao Yao. "Navigation Path Detection for Cotton Field Operator Robot Based on Horizontal Spline Segmentation." In Robotic Systems, 1326–40. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1754-3.ch063.

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Visual navigation is one of the fundamental techniques of intelligent cotton-picking robot. Cotton field composition is complex and the presence of occlusion and illumination makes it hard to accurately identify furrows so as to extract the navigation line. In this paper, a new field navigation path extraction method based on horizontal spline segmentation is presented. Firstly, the color image in RGB color space is pre-processed by the OTSU threshold algorithm to segment the binary image of the furrow. The cotton field image components are divided into four categories: furrow (ingredients include land, wilted leaves, etc.), cotton fiber, other organs of cotton and the outside area or obstructions. By using the significant differences in hue and value of the HSV model, the authors segment the threshold by two steps. Firstly, they segment cotton wool in the S channel, and then segment the furrow in the V channel in the area outside the cotton wool area. In addition, morphological processing is needed to filter out small noise area. Secondly, the horizontal spline is used to segment the binary image. The authors detect the connected domains in the horizontal splines, and merger the isolate small areas caused by the cotton wool or light spots in the nearby big connected domains so as to get connected domain of the furrow. Thirdly, they make the center of the bottom of the image as the starting point, and successively select the candidate point from the midpoint of the connected domain, according to the principle that the distance between adjacent navigation line candidate is smaller. Finally, the authors count the number of the connected domains and calculate the change of parameters of boundary line of the connected domain to make sure whether the robot reaches the outside of the field or encounters obstacles. If there is no anomaly, the navigation path is fitted by the navigation points using the least squares method. Experiments prove that this method is accurate and effective, which is suitable for visual navigation in the complex environment of a cotton field in different phases.
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Conference papers on the topic "HSV color model"

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Dhanesha, R., and Naika C. L. Shrinivasa. "Segmentation of Arecanut Bunches using HSV Color Model." In 2018 Third International Conference on Electrical, Electronics, Communication, Computer Technologies and Optimization Techniques (ICEECCOT). IEEE, 2018. http://dx.doi.org/10.1109/iceeccot43722.2018.9001632.

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Zhang, Yunzuo, Wenxuan Li, and Panliang Yang. "Shot Boundary Detection Based on HSV Color Model." In 2019 IEEE International Conference on Signal, Information and Data Processing (ICSIDP). IEEE, 2019. http://dx.doi.org/10.1109/icsidp47821.2019.9173070.

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Danxia Luo, Shuqing Li, and Chao Li. "An improved CLG Algorithm based on HSV color model." In 2010 3rd International Conference on Advanced Computer Theory and Engineering (ICACTE 2010). IEEE, 2010. http://dx.doi.org/10.1109/icacte.2010.5579414.

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Trambadia, Smit, and Hemant Mayatra. "Food detection on plate based on the HSV color model." In 2016 Online International Conference on Green Engineering and Technologies (IC-GET). IEEE, 2016. http://dx.doi.org/10.1109/get.2016.7916848.

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Al-Hetar, Abdulaziz M., Murad A. Rassam, Osama Shormani, Abdullah S. A. Salem, and Huthifa Al-Yousofi. "Color-based Object Categorization Model Using Fuzzy HSV Inference System." In 2019 First International Conference of Intelligent Computing and Engineering (ICOICE). IEEE, 2019. http://dx.doi.org/10.1109/icoice48418.2019.9035173.

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Zuraiyah, Tjut Awaliyah, Sarifuddin Madenda, Rina Noviana, and Ravi A. Salim. "Quran Tajweed Extraction and Segmentation Based on HSV Color Space Model." In 2018 Third International Conference on Informatics and Computing (ICIC). IEEE, 2018. http://dx.doi.org/10.1109/iac.2018.8780422.

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Shuhua, Li, and Guo Gaizhi. "The application of improved HSV color space model in image processing." In 2010 2nd International Conference on Future Computer and Communication. IEEE, 2010. http://dx.doi.org/10.1109/icfcc.2010.5497299.

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Joshi, Ketki, Ketaki Deshpande, Pranjali Aslekar, Sonam Bakliwal, and Parminder Kaur. "Sign Lang age Recogni ion sing Openc and HSV color Model." In 2020 International Conference on Smart Innovations in Design, Environment, Management, Planning and Computing (ICSIDEMPC). IEEE, 2020. http://dx.doi.org/10.1109/icsidempc49020.2020.9299600.

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Lih-Jen Kau and Tien-Lin Lee. "An HSV Model-Based Approach for the Sharpening of Color Images." In 2013 IEEE International Conference on Systems, Man and Cybernetics (SMC 2013). IEEE, 2013. http://dx.doi.org/10.1109/smc.2013.33.

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Zhao, Rujin, Jin Wang, Guobing Yu, Jie Zhong, Wulin Zhou, and Yihao Li. "A method of color correction of camera based on HSV model." In 7th International Symposium on Advanced Optical Manufacturing and Testing Technologies (AOMATT 2014), edited by Yadong Jiang, Junsheng Yu, and Bernard Kippelen. SPIE, 2014. http://dx.doi.org/10.1117/12.2070593.

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