Relevant bibliographies by topics / Grayscale image format

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Academic literature on the topic 'Grayscale image format'

Author: Grafiati
Published: 3 June 2025
Last updated: 13 July 2025

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Journal articles on the topic "Grayscale image format"

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Abdul-Wahab, Sami Ibrahim, and Jumaa Sartep2 Hind. "Transfer color from color image to grayscale image." International Journal of Engineering Research and Advanced Technology (IJERAT) 3, no. 3 (2017): 18–25. https://doi.org/10.5281/zenodo.438115.

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While there exist various techniques that can be used in coloring a grayscale image , in this paper we present new methods of colorization of grayscale image by transfer color between source color image to target grayscale image , generally colorizing grayscale image involves color space ,source color image and target greyscale image , here in this method we trying to minimize the human efforts needed in manually coloring the grayscale image , the human interaction is needed only to select a source color image , then the job of transfer color traits from source color image to grayscale image is done automatically by the proposed method. Here the method of colors transfer to grayscale image has been performed by using two different color spaces together in the coloring process, these color space are YCbCr and HSV color spaces along with different pixel window size start from (2 x 2), (3 x 3) up to (10 x 10). The proposed methods implemented in two file format types (JPEG and PNG) and on different types of imagesuch us (animals, Flower, plants).
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Wang, Fang Chao, Sen Bai, Bo Zhao, and Nan He. "Grayscale Image Compression and Encryption Based on Format Conversion." Applied Mechanics and Materials 411-414 (September 2013): 1193–96. http://dx.doi.org/10.4028/www.scientific.net/amm.411-414.1193.

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In this paper, we describe a novel encryption algorithm, which converts a greyscale image into a colored JPEG image. Firstly, it creates MCU (Minimum Coding Unit) of the colored JPEG image from the DU (Data Unit) of the greyscale image by the 8x8 construction matrix randomly. Secondly, it shuffles all the DUs with quantized DCT (Discrete Cosine Transform) coefficients according to a random ergodic matrix. Lastly, it rearranges the DUs as the format of the colored JPEG image and proceeds with the normal compression and encoding. The results show that the encryption speed of the algorithm is fast enough for real-time transmission and the encrypted image has almost the same size as original image after direct compression.
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Liu, Han-Ming, Zhao-Fa Liu, Zi Li, et al. "Genome-wide association study on color-image-based convolutional neural networks." PeerJ 13 (January 13, 2025): e18822. https://doi.org/10.7717/peerj.18822.

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Background Convolutional neural networks have excellent modeling abilities to complex large-scale datasets and have been applied to genomics. It requires converting genotype data to image format when employing convolutional neural networks to genome-wide association studies. Existing studies converting the data into grayscale images have shown promising. However, the grayscale image may cause the loss of information of the genotype data. Methods In order to make full use of the information, we proposed a new method, color-image-based convolutional neural networks, by converting the data into color images. Results The experiments on simulation and real data show that our method outperforms the existing methods proposed by Yue and Chen for converting data into grayscale images, in which the model accuracy is improved by an average of 7.61%, and the ratio of disease risk genes is increased by an average of 18.91%. The new method has better robustness and generalized performance.
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Lumbantobing, Theresia. "Implementasi Metode Felics Pada Kompresi Citra Format GIF." Jurnal Ilmu Komputer, Teknologi Dan Informasi 3, no. 1 (2025): 31–38. https://doi.org/10.62866/jurikti.v3i1.195.

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At this time, the increasingly rapid development of science and technology makes two-dimensional image files very necessary, where the resulting image size is large, requiring very large storage media, and other problems arise when exchanging data and information which increasingly consumes time and bandwidth. Therefore, a solution to the problem above emerged, namely by data compression. Data compression or data compression is a way in computer science to require smaller storage space, so that storage is more efficient. This is a compression method designed for grayscale images. The FELICS method presents a simpler system for lossless image compression that runs very quickly and only loses minimal compression efficiency. Implementation is the application or implementation, as an action to carry out the plan that has been made.
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Kirov, Nikolay, Milcho Tsvetkov, and Katya Tsvetkova. "Software Tools for Digitization of Astronomical Photographic Plates." Serdica Journal of Computing 6, no. 1 (2012): 67–76. http://dx.doi.org/10.55630/sjc.2012.6.67-76.

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In this paper we present tools for helping the process of digitization of astronomical photographic plates. The requirements of Virtual Observatory presume that any FITS file, which contains a digital image, has to be equipped with a complete header. Wide-Field Plate Database (WFPDB) offers most of the meta-data needed for the creation of FITS header. The header2011 software gives the user an appropriate tool for connecting WFPDB catalogues to digitized plate images. The use of modern scanners sometimes imposes conversion of files from the inner format of the scanner (or driver) into FITS format. The tif2fits software converts VueScan row-tiff format to FITS and also separates plate image and wedge image in case of scanning with grayscale wedge.
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Atika Sari, Christy, Eko Hari Rachmawanto, and Christanto Antonius Haryanto. "Cryptography Triple Data Encryption Standard (3DES) for Digital Image Security." Scientific Journal of Informatics 5, no. 2 (2018): 105–17. http://dx.doi.org/10.15294/sji.v5i2.14844.

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Advances in technology in the field of internet, making the Internet become the most popular data transmission media for now. This is certainly not free from the incidence of cyber crime, such as theft and data modification. Given the losses caused by data manipulation is very detrimental to the owner, then the original data can be misused in the cyber world. Cryptography offers an algorithm for randomizing data, so it can not be read by unauthorized people. The cryptography technique was implemented using Triple Data Encyption Standard (3DES) given the results of a randomized cryptographic algorithm, it is possible to arouse suspicion from the viewer. For that will be done the process of insertion of cryptographic files into another media in the form of images commonly referred to as steganography. The steganography technique that will be used is End of File (EOF). The combination of 3DES and EOF in the 64x64 pixel image with grayscale color format produces the fastest image processing time of 173.00192 seconds with the highest Peak Signal to Noise Ratio (PSNR) value of 25.0004 dB, while in the 128x128 pixel image with grayscale format has produced the highest PSNR 21.0084 dB.
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Juli Elprida Hutagalung, Mhd Ihsan Pohan, and Yuli Happy Marpaung. "Identifikasi Kesegaran Ikan Nila menggunakan Teknik Citra Digital." JUKI : Jurnal Komputer dan Informatika 2, no. 1 (2020): 6–10. http://dx.doi.org/10.53842/juki.v2i1.23.

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Fish contain many nutrients that are very beneficial for the body, but often fish are traded in a state of death as well as being alive. To observe the freshness of tilapia is done by the introduction of color changes that appear on digital images using the least squares method. The purpose of this research is to build an image management application system to detect the freshness of tilapia. The data used are 10 samples of tilapia images which are photographed every 1 hour for 15 hours and obtained 150 image data and then processed and analyzed using the least squares method. The first process begins with image processing by cropping at the edge of the eye of the original image and then proceed with resizing to 1000 x 1000 pixels and changing the image format to *. Png. After the image has been processed then the average value is calculated rata grayscale uses the 'rata_rata Gambar' application system and an equation is stored which is stored as training data on the application system. After the image has been processed then the image is input into the system, the image will be converted into grayscale form and displayed at a predetermined place together with the rgb and grayscale histograms and then calculated using the least squares method. The last process we do is matching the test image with the image stored as training data and we conclude whether the image is (very fresh, fresh, fresh enough, not fresh, or very not fresh), the percentage of freshness of the anchor fish, and the length of time the anchor fish dies. This study used 150 samples of fish images from fresh fish that were still very fresh until the fish were not very fresh (rotten).
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Zhang, Yue, and Ting Ting Gao. "VC-Based Rutting Digital Imaging Automatic Detection Technology Research and Design for Road Construction." Advanced Materials Research 461 (February 2012): 370–72. http://dx.doi.org/10.4028/www.scientific.net/amr.461.370.

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With the road construction, an automatic detection of road surface of rutting will be the main detection methods. VC-based digital imaging detection technology has an advantage of the vehicle, such as a simple structure, amount of data storage capacity, less affected by vehicle vibration. This article based on digital imaging technology detects grayscale bitmap format captured image information of the rutting. It focused on the grayscale bitmap image processing. The article shows that by generating curve can accurately reflect the actual situation of the road. And it can greatly improve the efficiency of road data and the accuracy of automatic detection.
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Murthy T. S., Deepthi, and Sadashivappa G. "Framework for comprehensive enhancement of brain tumor images with single-window operation." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 1 (2020): 801. http://dx.doi.org/10.11591/ijece.v10i1.pp801-808.

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Usage of grayscale format of radiological images is proportionately more as compared to that of colored one. This format of medical image suffers from all the possibility of improper clinical inference which will lead to error-prone analysis in further usage of such images in disease detection or classification. Therefore, we present a framework that offers single-window operation with a set of image enhancing algorithm meant for further optimizing the visuality of medical images. The framework performs preliminary pre-processing operation followed by implication of linear and non-linear filter and multi-level image enhancement processes. The significant contribution of this study is that it offers a comprehensive mechanism to implement the various enhancement schemes in highly discrete way that offers potential flexibility to physical in order to draw clinical conclusion about the disease being monitored. The proposed system takes the case study of brain tumor to implement to testify the framework.
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Deepthi, Murthy T. S., and G. Sadashivappa. "Framework for comprehensive enhancement of brain tumor images with single-window operation." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 1 (2020): 801–8. https://doi.org/10.11591/ijece.v10i1.pp801-808.

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Usage of grayscale format of radiological images is proportionately more as compared to that of colored one. This format of medical image suffers from all the possibility of improper clinical inference which will lead to error-prone analysis in further usage of such images in disease detection or classification. Therefore, we present a framework that offers single-window operation with a set of image enhancing algorithm meant for further optimizing the visuality of medical images. The framework performs preliminary pre-processing operation followed by implication of linear and non-linear filter and multi-level image enhancement processes. The significant contribution of this study is that it offers a comprehensive mechanism to implement the various enhancement schemes in highly discrete way that offers potential flexibility to physical in order to draw clinical conclusion about the disease being monitored. The proposed system takes the case study of brain tumor to implement to testify the framework.
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Book chapters on the topic "Grayscale image format"

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Veiga, Artur José Pires, Eduardo Silveira Bernardes, Daniela Andrade Monteiro Veiga, Iris Fernanda Silva Bonfim, Jaqueline Silva Portela, and Fabiana Santos Silva. "Morphometric analysis of the Serra do Sincorá Geopark, using remote sensing and GIS." In COLLECTION OF INTERNATIONAL TOPICS IN HEALTH SCIENCE- V1. Seven Editora, 2023. http://dx.doi.org/10.56238/colleinternhealthscienv1-041.

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The study analyzed the morphometric characteristics of the Chapada Diamantina relief, covering Andaraí, Mucugê, Lençóis and Palmeiras municipalities, which delimits the mountain range of Sincorá, a geopark proposal to be submitted to UNESCO in the coming years. The works were carried out at the Technical Drawing Laboratory in UESB (Universidade Estadual do Sudoeste da Bahia), using Remote Sensing and GIS (Geographic Information System). The orbital database used in raster format are the SRTM (Shuttle Radar Topograph System) elevation data with a grid of 30x30 meters and images from the LANDSAT 8 satellite, with a spatial resolution of 30 meters, bands 4-5-6, available in the USGS (United States Geological Survey) website service. Data in vector format were obtained from websites of Brazilian official institutes (EMBRAPA, IBGE, CPRM, MMA). The analysis first allowed to infer that the mountain range of Sincorá is oriented predominantly in the SW-NE direction, with 32 percent of its relief in this orientation; other alignments correspond to 19-12 percent of the total. Considering the altimetry, the predominant values were for elevations from 300 to 1300 meters, in 95% of the total area, although the maximum value found was 1700 meters of altitude. The relief was distributed as apartment surface, gently undulating, undulating, strongly undulating, mountainous and steep classes. The morphometric data of the relief were produced in 3D modeling, represented with texture from satellite images, grayscale, hypsometry, slope, shaded image and exposure of slopes, with spatial analysis. The results are expected to allow other researchers and technicians to work their planning and management actions with them, especially those from the region of geopark proposal.
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Suriyan, Kannadhasan, and Nagarajan R. "Recent Trends in Pattern Recognition." In Machine Learning Techniques and Industry Applications. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-5271-7.ch010.

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Character recognition is the technique of identifying characters that have been optically processed (OCR). OCR is a method of converting a wide range of texts, PDFs, and digital pictures into an American Standard Code for Information Interchange (ASCII) or other machine-editable format in which the data may be changed or searched. Many applications, such as OCR, document categorization, data mining, and others, have demanded recent improvements in pattern recognition. Document scanners, character recognition, language recognition, security, and bank identification all rely on OCR. There are two kinds of OCR systems: online character recognition and offline character recognition. Online OCR outperforms offline OCR because characters are processed as they are written, avoiding the first step of character identification. Offline OCR is separated into two types: printed and handwritten OCR. Offline OCR is often performed by scanning typewritten or handwritten characters into a binary or grayscale picture for processing by a recognition algorithm. Scanned papers have become more valuable than typical picture files as OCR technology has advanced, converting them into text contents that computers can identify. Over the traditional process of manually retyping, OCR discovers a superior approach of automatically putting data into an electronic database. The most common issue with OCR is segmentation of linked letters or symbols. The accuracy of the OCR is proportional to the input image.
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R., Chandra Prabha, and Shilpa Hiremath. "Computer Processing of an Image." In Handbook of Research on Deep Learning-Based Image Analysis Under Constrained and Unconstrained Environments. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-6690-9.ch001.

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In this chapter, the authors have briefed about images, digital images, how the digital images can be processed. Image types like binary image, grayscale image, color image, and indexed image and various image formats are explained. It highlights the various fields where digital image processing can be used. This chapter introduces a variety of concepts related to digital image formation in a human eye. The mechanism of the human visual system is discussed. The authors illustrate the steps of image processing. Explanation on different elements of digital image processing systems like image acquisition, and others are also provided. The components required for capturing and processing the image are discussed. Concepts of image sampling, quantization, image representation are discussed. It portrays the operations of the image during sampling and quantization and the two operations of sampling which is oversampling and under-sampling. Readers can appreciate the key difference between oversampling and under-sampling applied to digital images.
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Niimi, Michiharu, and Hideki Noda. "Introduction to Image Steganography and Steganalysis." In Advances in Multimedia and Interactive Technologies. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2217-3.ch010.

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This chapter reviews information hiding methods, with a focus on steganography and steganalysis. First, the authors summarize image data structures and image formats required by computers and the Internet. They then introduce several information hiding methods based on image formats including lossless (non-compression based), limited color-based image data, JPEG, and JPEG2000. The authors describe a steganographic method in detail, which is based on image segmentation using a complexity measure. They also introduce a method for applying this to palette-based image formats, reversible information hiding for grayscale images, and JPEG2000 steganography. The steganographic methods for JPEG and JPEG2000 described in this chapter give particular consideration to the naturalness of cover data. In the steganalysis section, the authors introduce two methods, i.e., a specific steganalysis method for LSB steganography and Bit-Plane Complexity Segmentation (BPCS) stegnography.
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Conference papers on the topic "Grayscale image format"

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Zhao, Shaofang, Xiaoyan Chen, Ziwen zheng, and Qang Lin. "Classifying SPECT Bone Metastasis Images in Grayscale Format with VGGNets." In 2021 International Conference on Communications, Information System and Computer Engineering (CISCE). IEEE, 2021. http://dx.doi.org/10.1109/cisce52179.2021.9446029.

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A. Noever, David, and Samantha E. Miller Noever. "Image Classifiers for Network Intrusions." In 9th International Conference of Security, Privacy and Trust Management (SPTM 2021). AIRCC Publishing Corporation, 2021. http://dx.doi.org/10.5121/csit.2021.110504.

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This research recasts the network attack dataset from UNSW-NB15 as an intrusion detection problem in image space. Using one-hot-encodings, the resulting grayscale thumbnails provide a quarter-million examples for deep learning algorithms. Applying the MobileNetV2’s convolutional neural network architecture, the work demonstrates a 97% accuracy in distinguishing normal and attack traffic. Further class refinements to 9 individual attack families (exploits, worms, shellcodes) show an overall 56% accuracy. Using feature importance rank, a random forest solution on subsets show the most important sourcedestination factors and the least important ones as mainly obscure protocols. The dataset is available on Kaggle.
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Dmitriev, E. V., T. V. Kondranin, P. G. Melnik, and S. A. Donskoy. "Statistical texture analysis of forest areas from very high spatial resolution satellite images." In Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes 2021. Crossref, 2021. http://dx.doi.org/10.25743/sdm.2021.64.23.009.

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Aerospace images with a spatial resolution of less than 1 m are actively used by regional services to obtain and update information about various environmental objects. Considerable efforts are being devoted to the development of remote sensing methods for forest areas. The structure of the forest canopy depends on various parameters, most of which are determined by ground-based methods during forest management works. Remote sensing methods for assessing the structural parameters of forest stands are based on texture analysis of panchromatic and multispectral images. A statistical approach is often used to extract texture features. The basis of this approach is the description of the distributions characterizing the mutual arrangement of image pixels in grayscale. This paper compares the effectiveness of matrix based statistical methods for extracting textural features for solving the problem of classifying various natural and manmade objects, as well as structures of the forest canopy. We consider statistics of various orders based on estimates of the distributions of gray levels, as well as the mutual occurrence, frequency, difference and structuring of gray levels. The results of assessing the informativeness of statistical textural characteristics in determining various structures of the forest canopy are presented. Dependences of the classification results on the choice of distribution parameters are determined. For the quantitative validation of the results obtained, data from ground surveys and expert visual classification of very high resolution WorldView-2 images of the territories of Savvatyevkoe and Bronnitskoe forestries are used.
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