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Journal articles on the topic 'Genetic Algorithm and Image Processing'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Hassan, Raghad Mahdie, and Luma Salal Hassan. "Assessments Image Segmentation Using Genetic Algorithm." Al-Furat Journal of Innovations in Electronics and Computer Engineering 3, no. 2 (2024): 352–63. http://dx.doi.org/10.46649/fjiece.v3.2.23a.2.6.2024.

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Image segmentation is a crucial technique for processing images. It is a challenging task to process images, and the quality of the segmentation process affects the following assignments, which include classification, object recognition, feature extraction, and object detection.It's a significant phase of a system for computer vision. Image segmentation is the basic problem in many applications for image processing. Over time, image segmentation has gotten more challenging due to its extensive use in numerous applications. It is the procedure of segmenting the image into various areas by using

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Guan, Xiao Wei, and Xia Zhu. "Image Segmentation Research Based on Genetic Algorithm." Advanced Materials Research 403-408 (November 2011): 1622–25. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.1622.

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As one of the difficulties and hot of computer vision and image processing, Image segmentation is highly valued by the research workers. Yet there is no image segmentation algorithm which is generic, and it is difficult to obtain an optimal feature representation method. In this paper, genetic algorithm (GA) has proposed to segment the image. GA algorithm can improve the efficiency and quality of the picture some extent through the experimental results. The algorithm has some versatility, as long as the corresponding parameters are adjusted, it can also handle the other images. The results sho

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Riwanto, Yudha, and Enda Putri Atika. "Performance Analysis of Genetic Algorithms and KNN Using Several Different Datasets." Internet of Things and Artificial Intelligence Journal 4, no. 3 (2024): 526–31. http://dx.doi.org/10.31763/iota.v4i3.767.

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This research aims to increase the accuracy of the classification of mango, corn, and potato leaf types using an approach involving feature selection with a genetic algorithm (Genetic Algorithm), classification with K-Nearest Neighbors (KNN), and image processing in the HSV color space (Hue, Saturation). , Value). The dataset used consists of more than 1500 image samples for each type of leaf, with a total of 10 tests carried out. The research process begins with processing leaf images in HSV color space to extract more representative color information. Next, a genetic algorithm is applied to

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Agarwal, Ritu, and Mallika Pant. "Image tampering detection using genetic algorithm." MATEC Web of Conferences 277 (2019): 02026. http://dx.doi.org/10.1051/matecconf/201927702026.

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As digital images become an indispensable source of information, the authentication of digital images has become crucial. Various techniques of forgery have come into existence, intrusive, and non-intrusive. Image forgery detection hence is becoming more challenging by the day, due to the unwavering advances in image processing. Therefore, image forensics is at the forefront of security applications aiming at restoring trust and acceptance in digital media by exposing counterfeiting methods. The proposed work compares between various feature selection algorithms for the detection of image forg

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A., D. Chitra* Dr. P. Ponmuthuramalingam. "AN ENHANCED HYBRID CUCKOO SEARCH AND GENETIC ALGORITHM USING HAAR-LIKE FEATURE FOR SURVEILLANCE VIDEOS." Global Journal of Engineering Science and Research Management 4, no. 7 (2017): 74–84. https://doi.org/10.5281/zenodo.832647.

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This paper is mainly focused on image processing concept which is used in surveillance videos for security purpose. Image processing technique involves dispensation of image using a mixture of mathematical functions in which image or video is given as input and the extent to which the image is matched is given as output. The main problem found in this paper are edge detection and noise removal in images. Initially this research paper is compared with cuckoo search and genetic algorithm. Then these two algorithms are combined together as an hybrid CS - GA Algorithm and finally the result of thi

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Gorokhovskyi, Semen, and Andrii Moroz. "Image Segmentation Using Genetic Algorithms." NaUKMA Research Papers. Computer Science 4 (December 10, 2021): 52–55. http://dx.doi.org/10.18523/2617-3808.2021.4.52-55.

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Image segmentation is a crucial step in the image processing and analysis process. Image segmentation is the process of splitting one image into many segments. Image segmentation divides images into segments that are more representative and easier to examine. Individual surfaces or items can be used as such pieces. The process of image segmentation is used to locate objects and their boundaries.Genetic algorithms are stochastic search methods, the work of which is taken from the genetic laws, natural selection, and evolution of organisms. Their main attractive feature is the ability to solve c

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Li, Xiao Guang. "Research on the Automatic Multilevel Thresholding for Athletic Image Segmentation Based on Block Sampling and Genetic Algorithm." Advanced Materials Research 791-793 (September 2013): 2007–12. http://dx.doi.org/10.4028/www.scientific.net/amr.791-793.2007.

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The research on new image segmentation algorithm is a very meaningful work in the processing of image. In the process, it will produce large amount of data redundancy. The efficient algorithm not only can greatly improve the quality of image treatment but also can greatly reduce the time and cost of the treatment. In this context, the paper analyzes several image processing algorithms commonly used in recent years and presents a new computer image processing algorithm--AMT-GA algorithm. In order to verify the effectiveness of AMT-GA algorithm, this paper takes the process of athletics image fo

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J. Hemalatha, R., Dr V. Vijaybaskar, A. Josephin Arockia Dhivya, and . "Early detection of joint abnormalities from ultrasound images." International Journal of Engineering & Technology 7, no. 2.25 (2018): 105. http://dx.doi.org/10.14419/ijet.v7i2.25.16569.

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Musculoskeletal ultrasound is effective for the early detection of joint abnormalities like erosion, effusion, synovitis and inflammation. Computer software is developed for segmentation of joint ultrasound image to diagnose the defect. The objective of developing this paper is to achieve early diagnosis of joint disorders by segmentation of ultrasound image with different algorithms. Ultrasound machine with high resolution probe can be used for development & findings of joints by the orthopaedician, rheumatologist and sports physician. These find-ings are done by processing the ultrasound

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He, Yun, Yan Gang Wu, Jia Lin Tian, and Wen Xu. "Image Restoration of Depth of Field Extension Imaging System Based on Genetic Algorithm." Applied Mechanics and Materials 539 (July 2014): 131–35. http://dx.doi.org/10.4028/www.scientific.net/amm.539.131.

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Genetic algorithm is a search algorithm based on genetic mechanism and natural selection. It has been widely applied to research fields including image processing field. The paper improves standard genetic algorithm and improves the arithmetic speed of the algorithm, which achieves better image restoration effect. And the paper compares the image restoration quality of traditional algorithm, standard genetic algorithm and improved genetic algorithm to prove the feasibility of applying genetic algorithm to image restoration.

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Wei, Wei, Liang Liu, Zhong Qin Hu, and Yu Jing Zhou. "Rigid Medical Image Registration Based on Genetic Algorithms and Mutual Information." Applied Mechanics and Materials 665 (October 2014): 712–17. http://dx.doi.org/10.4028/www.scientific.net/amm.665.712.

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With the variety of medical imaging equipment’s application in the medical process,medical image registration becomes particularly important in the field of medical image processing,which has important clinical diagnostic and therapeutic value. This article describes the matrix conversion method of the rigid registration model, the basic concepts and principles of the mutual information algorithm ,the basic idea of genetic algorithms and algorithm’s flow , and the application of the improved genetic algorithms in practice. The rigid registration of two CT brain bones images uses mutual informa

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Kawamoto, Kazuhiko. "Special Issue on Advances on Intelligent Multimedia Processing." Journal of Advanced Computational Intelligence and Intelligent Informatics 14, no. 2 (2010): 121. http://dx.doi.org/10.20965/jaciii.2010.p0121.

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As computer and sensor technology advances make increasing amounts of multimedia data available, multimedia processing methodologies are needed for multimodal data fusion, efficient data processing, information extraction, and added-value data generation. This special issue introduces the following latest practical developments in image processing, acoustical signal processing, pattern recognition, data mining, and visualization: S. Kobashi et al. propose a robust algorithm for reconstructing total knee arthroplasty implants from X-ray cone-beam images. Y. Hatakeyama et al. propose an algorith

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Mondal, Probir, Debranjan Pal, Krishnendu Basuli, and Pratyay Banerjee. "Visualizing Genetic Patterns: A Comparative Analysis of DNA Sequences Through Image Processing." International Journal of Microsystems and IoT 2, no. 2 (2024): 586–90. https://doi.org/10.5281/zenodo.10803111.

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A comparative analysis of DNA sequence is investigated through Image Processing. The underlying algorithm transforms, in a novel way, genetic data into images. The information is encoded by using the pixel intensities representing the four constituent nucleotide bases viz. A, T, C and G. These sequences are then employed to generate visual representations, facilitating an intuitive understanding of complex genetic information. Our study integrates machine learning techniques to compare and cluster these DNA sequence-based images, offering a powerful tool for classification. By leveraging machi

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Mutar, Jinan Redha. "Study of Methodologyof Optimizing Image Segmentation and Processing Using Genetic Algorithm." International Journal of Advances in Scientific Research and Engineering 08, no. 12 (2022): 15–21. http://dx.doi.org/10.31695/ijasre.2022.8.12.3.

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In the literature, several worksfocal point on the description of contrast metrics and standards that allow to count the overall an image processing algorithm performance. These assessment standards can be investigated to outline new photo processing algorithms by way of optimizing them. In this work, we suggest a universal scheme to phasephotographswith the aid of a genetic algorithm. The developed approach makes use of an estimation standard which counts the first-class of a photo segmentation outcome. The suggested type segmentationapproach can combine a local ground reality when it is acce

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Wu, Long, Jie Chen, Shuyu Chen, et al. "Hybrid Dark Channel Prior for Image Dehazing Based on Transmittance Estimation by Variant Genetic Algorithm." Applied Sciences 13, no. 8 (2023): 4825. http://dx.doi.org/10.3390/app13084825.

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Image dehazing has always been one of the main areas of research in image processing. The traditional dark channel prior algorithm (DCP) has some shortcomings, such as incomplete fog removal and excessively dark images. In order to obtain haze-free images with high quality, a hybrid dark channel prior (HDCP) algorithm is proposed in this paper. HDCP first employs Retinex to remove the interference of the illumination component. The variant genetic algorithm (VGA) is then used to obtain the guidance image required by the guided filter to optimize the atmospheric transmittance. Finally, the modi

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K., Pavithra. "Analytical Method of Multi-Objective Genetic Algorithm with Multi-Objective Messy Genetic Algorithm in Satellite Image Segmentation." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 3, no. 3 (2018): 168–73. https://doi.org/10.5281/zenodo.4301122.

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Image can be dividing into different Segmentation. In image processing , the important task is Segmentation process methods. This method involves such as K-means clustering, watershed segmentation, Fuzzy c-Means, Iterative Self Organizing Data. Clustering methods depends powerfully on the selection of the primary spectral signatures which represents initial cluster centers. Normally, this is either done physically or erratically based on statistical operations. In this case the outcome is random and sometime inaccurate. In base paper an unsupervised method based on Multi-Objective Genetic Algo

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Li, Mingfeng. "Comprehensive Review of Backpropagation Neural Networks." Academic Journal of Science and Technology 9, no. 1 (2024): 150–54. http://dx.doi.org/10.54097/51y16r47.

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The Backpropagation Neural Network (BPNN) is a deep learning model inspired by the biological neural network. Introduced in the 1980s, the BPNN quickly became a focal point in neural network research due to its outstanding learning capability and adaptability. The network structure consists of input, hidden, and output layers, and it optimizes weights through the backpropagation algorithm, widely applied in image recognition, speech processing, natural language processing, and more. The mathematical model of neurons describes the relationship between input and output, and the training process

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Tang, Jinyu. "An Optimized Digital Image Processing Algorithm for Digital Oil Painting." Mobile Information Systems 2022 (May 31, 2022): 1–10. http://dx.doi.org/10.1155/2022/4956839.

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Human civilization’s accomplishments have grown with the passage of time and the advancement of society. With the fast growth of computer networks and information technology, the conventional method of information transmission based on words cannot fulfill the demands of people in the current era. As a result, in this age of extensive information and image processing techniques, images as a means of information sharing are becoming increasingly popular. As we know, digital image processing knowledge has a far-reaching impact in the field of artistic creation, among which the creation of oil pa

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Tahir KASIM, Ghada Mohammad, Zahraa Mazin ALKATTAN, and Nadia Maan MOHAMMED. "Hybrid System for Image Restoration." International Research Journal of Innovations in Engineering and Technology 08, no. 01 (2024): 168–77. http://dx.doi.org/10.47001/irjiet/2024.801020.

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The image processing field is considered one of the highly sensitive fields for accuracy due to the quality of the processing in view of the visual view of the user and due to the development in modern means of communication and the use of these means in the transfer of images and the impact of these means on several factors, including external, including those related to the quality of the source signal and the impact of the transmitted images by these conditions, digital correction processes have emerged to reach a high quality of the received image. Most of the studies and research on digit

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WANG, Li, and Wei WANG. "Hyperspectral image compressed processing: Evolutionary multi-objective optimization sparse decomposition." PLOS ONE 17, no. 4 (2022): e0267754. http://dx.doi.org/10.1371/journal.pone.0267754.

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In the compressed processing of hyperspectral images, orthogonal matching pursuit algorithm (OMP) can be used to obtain sparse decomposition results. Aimed at the time-complex and difficulty in applying real-time processing, an evolutionary multi-objective optimization sparse decomposition algorithm for hyperspectral images is proposed. Instead of using OMP for the matching process to search optimal atoms, the proposed algorithm explores the idea of reference point non-dominated sorting genetic algorithm (NSGA) to optimize the matching process of OMP. Take two objective function to establish t

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Chen, Shou-Ming, and Jun-Hui Zhang. "Genetic Algorithm in Data Mining of Colorectal Images." Computational and Mathematical Methods in Medicine 2021 (October 15, 2021): 1–8. http://dx.doi.org/10.1155/2021/3854518.

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There is currently no effective analytical method in colorectal image analysis, which leads to certain errors in colorectal image analysis. In order to improve the accuracy of colorectal imaging detection, this study used a genetic algorithm as the data mining algorithm and combined it with image processing technology to perform image analysis. At the same time, combined with the actual requirements of image detection, the gray theory model is used as the basic theory of image processing, and the image detection prediction model is constructed to predict the data. In addition, in order to stud

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Liu, Hai Yan. "Application of Genetic Algorithm to Image Segmentation." Applied Mechanics and Materials 685 (October 2014): 642–45. http://dx.doi.org/10.4028/www.scientific.net/amm.685.642.

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Image segmentation is very important in image analysis that needs to separate the related area for the general target distinguishing and analyzing an image, and it can make further use of the target, such as characteristic pick-up and measure on the basis of image processing disposal. In this dissertation, image segmentation based on genetic algorithm will be described. The selection of threshold and the process about image segmentation based on genetic algorithm are described. Finally, image segmentation based on genetic algorithm is used on a picture by Matlab, the result can be accepted. Th

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Gdeeb, Rasha Talib. "Using Genetic Algorithms to Segment Images: A Review." Al-Kitab Journal for Pure Sciences 7, no. 2 (2023): 1–15. http://dx.doi.org/10.32441/kjps.07.02.p1.

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The genetic algorithm plays a pivotal role in image processing, particularly in the critical stage of image segmentation. The process of segmenting photographs is an essential method in the field. Identifying objects, extracting features for object recognition, and classifying are integral components of image processing. However, the effectiveness of these activities relies on the quality of the operations performed. The work at hand in the domain of image processing is notably arduous and intricate. The segmentation of photos cannot be consistently achieved through the utilization of a singul

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Hajira Be, A. B. "Feature Selection and Classification with the Annealing Optimization Deep Learning for the Multi-Modal Image Processing." Journal of Computer Allied Intelligence 2, no. 3 (2024): 55–66. http://dx.doi.org/10.69996/jcai.2024015.

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This paper investigates and compares various feature selection algorithms within the context of image processing across multiple datasets. The study evaluates Seahorse Annealing Optimization for Feature Selection (SAO-FS), Genetic Algorithms (GA), CNN + Feature Fusion Network, and Lasso Regression on distinct image datasets—medical images, satellite images, MRI scans, and microscopy images. Performance metrics including accuracy, precision, recall, and computational time are analyzed to assess the efficacy of each algorithm in optimizing feature subsets for classification tasks. SAO-FS demonst

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Et. al., Vigneshwari K,. "Genetic Algorithm Based Fuzzy Local Informationc-Means (Gaflicm) Clustering Algorithm And Hybrid Kernel Convolution Neural Network (Hkcnn) With Distributed Processing Framework For Brain Mri Images." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 10 (2021): 5639–56. http://dx.doi.org/10.17762/turcomat.v12i10.5375.

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Cancer is the large important origin of casualty in today world. Among many cancers, brain cancer has been becomes one of the lowest living rate. It is formed based on the brain tumor. However brain tumors are able to have diverse categories based on their shape, texture, and position. Appropriate identification and retrieval of the tumor types create potential the doctor to compose the right cure option and assist keep the patient's life. Image processing has gained wide attention in medical analysis and health in recently. In general image processing methods, brain Magnetic Resonance Imaging

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Khudov, Hennadii, Oleksandr Makoveichuk, Temir Kalimulin, Vladyslav Khudov, and Nazar Shamrai. "THE METHOD FOR APPROXIMATING THE EDGE DETECTION CONVOLUTIONAL OPERATOR USING A GENETIC ALGORITHM FOR SEGMENTATION OF COMPLEX-STRUCTURED IMAGES." Advanced Information Systems 8, no. 4 (2024): 5–12. http://dx.doi.org/10.20998/2522-9052.2024.4.01.

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The subject matter of the study in the article is the method for approximating the convolutional operator for edge detection using a genetic algorithm for segmentation of complex-structured images. The goal is to develop a method for approximating the convolutional operator for edge detection using a genetic algorithm for the segmentation of complex-structured images. The tasks are: analysis of known methods of segmentation of optoelectronic images, development of a method for approximating the edge detection convolutional operator using a genetic algorithm for segmenting complex-structured im

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Xu, Taotao, Lijian Yao, Lijun Xu, Qinhan Chen, and Zidong Yang. "Image Segmentation of Cucumber Seedlings Based on Genetic Algorithm." Sustainability 15, no. 4 (2023): 3089. http://dx.doi.org/10.3390/su15043089.

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To solve the problems of the low target-positioning accuracy and weak algorithm robustness of target-dosing robots in greenhouse environments, an image segmentation method for cucumber seedlings based on a genetic algorithm was proposed. Firstly, images of cucumber seedlings in the greenhouse were collected under different light conditions, and grayscale histograms were used to evaluate the quality of target and background sample images. Secondly, the genetic algorithm was used to determine the optimal coefficient of the graying operator to further expand the difference between the grayscale o

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Preetam, Singh* Mr Jatinder Sharma. "A REVIEW PAPER ON IMAGE DENOISING BY LOW RANK MATRIX DECOMPOSITION ANDGENETIC ALGORITHM." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 5, no. 7 (2016): 166–681. https://doi.org/10.5281/zenodo.56923.

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A great challenge in the field of image processing nowadays is image denoising. Although, there have beenproposed various methods and algorithms for the same, but,most of them have not attained the desirable results. Theperformance does not match with the assumed one.In the field of image denoising, nonlocal image denoising algorithm is a nonlinear, space average denoising algorithm, it will not cause boundary blurred, and it is an effective denoising algorithm. But its application still has limitations because of it taking much longer time, in this paper, the method was improved, image signal

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Wu, Yong Zhuo, Zhen Tu, and Lei Liu. "Local Statistic Enhancement of Digital Image Based on Genetic Algorithm." Applied Mechanics and Materials 427-429 (September 2013): 1836–40. http://dx.doi.org/10.4028/www.scientific.net/amm.427-429.1836.

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Iamge repair using the digital image processing technology has become a new research point in computer application. A novel method of local statistic enhancement based on genetic algorithm is proposed in this paper for the image enhancement. The modified amplified function are used as the jugement criterion, and the optimal paremeters are searched by the genetic algorithm. Experimental results show that the quality of images is improved dramatically by using this method.

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Si, Lipeng, Xiuhua Hu, and Baolong Liu. "Image Matching Algorithm Based on the Pattern Recognition Genetic Algorithm." Computational Intelligence and Neuroscience 2022 (March 9, 2022): 1–9. http://dx.doi.org/10.1155/2022/7760437.

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Image matching is an important topic in image processing. Matching technology plays an important role in and is the basis for image understanding. In order to solve the shortcomings of slow image matching and low matching accuracy, a matching method based on improved genetic algorithm is proposed. The main improvement of the algorithm is the use of self-identifying crossover operators for crossover operations to avoid premature population maturity. According to the characteristics of the image data, new intersection and mutation operators are defined by the new coding method. The sampling meth

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ZHENG, Guang, and Yiran WANG. "Adaptive Genetic Algorithm Based on Chaotic Intelligent Algorithm to Image Restoration Research." International Journal of Signal Processing, Image Processing and Pattern Recognition 9, no. 7 (2016): 305–14. http://dx.doi.org/10.14257/ijsip.2016.9.7.27.

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C, Nithyasree, Stanley D, and Subalakshmi K. "Brain Tumor Detection using Image Processing." International Journal on Cybernetics & Informatics 10, no. 2 (2021): 319–25. http://dx.doi.org/10.5121/ijci.2021.100235.

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Brain tumor extraction and its analysis are challenging tasks in medical image processing because brain image is complicated .Segmentation plays a very important role in the medical image processing.In that way MRI (magnetic resonance imaging )has become a useful medical diagnostic tool or the diagnosis o brain & other medical images.In this project, we are presenting a comparative study of three segmentation methods implemented or tumor detection .The method includes kmeans clustering using watershed algorithm . Optimized k-means and optimized c-means using genetic algorithm.

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Raihan, Md, Kh Mohaimenul, and Md Mehedi. "Data Security Throws Image processing by Blowfish Algorithm, Genetic Algorithm and LSB." International Journal of Computer Applications 148, no. 1 (2016): 1–3. http://dx.doi.org/10.5120/ijca2016909946.

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Mishra, Shashwati, and Mrutyunjaya Panda. "Medical Image Thresholding Using Genetic Algorithm and Fuzzy Membership Functions." International Journal of Fuzzy System Applications 8, no. 4 (2019): 39–59. http://dx.doi.org/10.4018/ijfsa.2019100103.

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Thresholding is one of the important steps in image analysis process and used extensively in different image processing techniques. Medical image segmentation plays a very important role in surgery planning, identification of tumours, diagnosis of organs, etc. In this article, a novel approach for medical image segmentation is proposed using a hybrid technique of genetic algorithm and fuzzy logic. Fuzzy logic can handle uncertain and imprecise information. Genetic algorithms help in global optimization, gives good results in noisy environments and supports multi-objective optimization. Gaussia

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Kulkarni, Dr Jyoti S. "Genetic Algorithm Approach for Image Fusion: A Simple Method and Block Method." International Journal of Innovative Technology and Exploring Engineering 11, no. 6 (2022): 16–21. http://dx.doi.org/10.35940/ijitee.f9895.0511622.

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The sensors available nowadays are not generating images of all objects in a scene with the same clarity at various distances. The progress in sensor technology improved the quality of images over recent years. However, the target data generated by a single image is limited. For merging information from multiple input images, image fusion is used. The basis of image fusion is on the image acquisition as well as on the level of processing and under this many image fusion techniques are available. Several input image acquisition techniques are available such as multisensor, multifocus, and multi

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Dr., Jyoti S. Kulkarni. "Genetic Algorithm Approach for Image Fusion: A Simple Method and Block Method." International Journal of Innovative Technology and Exploring Engineering (IJITEE) 11, no. 6 (2022): 16–21. https://doi.org/10.35940/ijitee.F9895.0511622.

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<strong>Abstract:</strong> The sensors available nowadays are not generating images of all objects in a scene with the same clarity at various distances. The progress in sensor technology improved the quality of images over recent years. However, the target data generated by a single image is limited. For merging information from multiple input images, image fusion is used. The basis of image fusion is on the image acquisition as well as on the level of processing and under this many image fusion techniques are available. Several input image acquisition techniques are available such as multise

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Rasika, Joat, A. P. Thakare Dr., Ketaki Kalele Dr., and Viashali Thakare Dr. "Genetic Programming Approach for Oral Cancer Detection and its Image Restoration." International Journal of Trend in Scientific Research and Development 2, no. 3 (2018): 2422–26. https://doi.org/10.31142/ijtsrd12787.

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Cancer is one of the leading causes of death in developing countries. Cancers are of different types like breast cancer, lung cancer, skin cancer and so on. Oral Cancer is one of the types of cancers. Oral cancer is a very common type of cancer. This Oral Cancer is observed in both males as well as females. It is a big challenge to detect Oral Cancer. This is a time consuming process in medical image processing. Detection and prevention of oral cancer at early stage is critical. But it increases the chances of survival. This work presents the detection of oral cancers using Image Processing. C

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Roy, Abhisek, Pranab Kanti Roy, Anirban Mitra, et al. "Artificial bee colony-based nonrigid demons registration." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 4 (2024): 3951. http://dx.doi.org/10.11591/ijece.v14i4.pp3951-3961.

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The artificial bee colony (ABC) algorithm has gained popularity in recent years for its ability to solve optimization problems. The accuracy and resilience of ABC-based image processing techniques have demonstrated encouraging outcomes. The ABC method is an excellent solution for image processing issues since it has the ability to swiftly and effectively explore the search space. The current research intends to address image registration issues by refining the existing image registration strategy using ABC algorithm. The process of nonrigid demons registration is frequently employed in the pro

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Xi, Erhui, and Jiali Zhang. "Research on Image Deblurring Processing Technology Based on Genetic Algorithm." Journal of Physics: Conference Series 1852, no. 2 (2021): 022042. http://dx.doi.org/10.1088/1742-6596/1852/2/022042.

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Marwan, Ali Shnan, H. Rassem Taha, and Saradatul Akmar Zulkifli Nor. "Facial image retrieval on semantic features using adaptive mean genetic algorithm." TELKOMNIKA Telecommunication, Computing, Electronics and Control 17, no. 2 (2019): 882–96. https://doi.org/10.12928/TELKOMNIKA.v17i2.3774.

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The emergence of larger databases has made image retrieval techniques an essential component and has led to the development of more efficient image retrieval systems. Retrieval can either be content or text-based. In this paper, the focus is on the content-based image retrieval from the FGNET database. Input query images are subjected to several processing techniques in the database before computing the squared Euclidean distance (SED) between them. The images with the shortest Euclidean distance are considered as a match and are retrieved. The processing techniques involve the application of

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Liu, Xiao Jun. "Fire Detection Technology Based on Infrared Image Processing." Applied Mechanics and Materials 347-350 (August 2013): 3426–30. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.3426.

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This paper proposes a method to detect fire by processing the images captured by an CCD camera with infrared filter. First, the flame objects are detected by using two consecutive frames difference and background difference. Using genetic algorithm to optimize the threshold, the image is segmented by using Ostu. The boundary chain code is acquired on the basis of extracting flame contour. Lastly, shape feature, change feature and edge jitter feature are used to judge whether the fire exists. This method suppresses visible light interference. The experiment results show that the algorithm has h

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Song, Xiao Ling. "A Novel Modified Algorithm for Local Statistic Enhancement." Advanced Materials Research 926-930 (May 2014): 2910–13. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.2910.

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Image repair using the digital image processing technology has become a new hot point in the cultural relic protection. To study of ancient fresco restoration techniques, A novel algorithm of local statistic enhancement image is proposed in this paper for the reparation of ancient fresco. The modified amplified function and the rubber band conversion algorithm are used as the jugement criterion, and the optimal paremeters are searched by the genetic algorithm (GA). Experimental results show that the quality of images is improved compared with the traditional.

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K., Beulah Suganthy. "Identification of Disease in Leaves using Genetic Algorithm." International Journal of Trend in Scientific Research and Development 3, no. 3 (2019): 1264–67. https://doi.org/10.31142/ijtsrd22901.

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Plant disease is an impairment of normal state of a plant that interrupts or modifies its vital functions. Many leaf diseases are caused by pathogens. Agriculture is the mains try of the Indian economy. Perception of human eye is not so much stronger so as to observe minute variation in the infected part of leaf. In this paper, we are providing software solution to automatically detect and classify plant leaf diseases. In this we are using image processing techniques to classify diseases and quickly diagnosis can be carried out as per disease. This approach will enhance productivity of crops.

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Zhao, Jing. "Art Visual Image Transmission Method Based on Cartesian Genetic Programming." Scientific Programming 2021 (November 30, 2021): 1–10. http://dx.doi.org/10.1155/2021/4628563.

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Because most of the traditional artistic visual image communication methods use the form of modeling and calculation, there are some problems such as long image processing time, low success rate of image visual communication, and poor visual effect. An artistic visual image communication method based on Cartesian genetic programming is proposed. The visual expression sensitivity difference method is introduced to process the image data, the neural network is used to identify the characteristics of the artistic visual image, the midpoint displacement method is used to remove the folds of the ar

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Yang, Zeyin. "Application and Development of Digital Enhancement of Traditional Sculpture Art." Scientific Programming 2022 (February 3, 2022): 1–8. http://dx.doi.org/10.1155/2022/9095577.

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Sculpture art, as an important carrier of spiritual civilization, also portrays a prosperous scene as an industry with urban and cultural development. Three-dimensional technology offers a new platform for sculpture creation, allowing for the digitization of sculpture works via electronic information technology, and the display of sculpture works in front of people via displays, facilitating the exchange and dissemination of information and promoting the growth and progress of the entire sculpture creation industry. We plan to use digital enhancement technology to conduct small-scale creation

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Kong, Luoyi, Mohan Huang, Lingfeng Zhang, and Lawrence Wing Chi Chan. "Enhancing Diagnostic Images to Improve the Performance of the Segment Anything Model in Medical Image Segmentation." Bioengineering 11, no. 3 (2024): 270. http://dx.doi.org/10.3390/bioengineering11030270.

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Medical imaging serves as a crucial tool in current cancer diagnosis. However, the quality of medical images is often compromised to minimize the potential risks associated with patient image acquisition. Computer-aided diagnosis systems have made significant advancements in recent years. These systems utilize computer algorithms to identify abnormal features in medical images, assisting radiologists in improving diagnostic accuracy and achieving consistency in image and disease interpretation. Importantly, the quality of medical images, as the target data, determines the achievable level of p

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Feng Shou, Zhang, Dong Fang, Liu Jian Ting, and Meng Xin. "An improved method of microscopic image segmentation." MATEC Web of Conferences 176 (2018): 01041. http://dx.doi.org/10.1051/matecconf/201817601041.

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In order to improve the effectiveness and accuracy of image processing in modern medical inspection, a segmentation image optimization algorithm of improved two-dimensional maximum entropy threshold based on genetic algorithm combined with mathematical morphology is proposed, in view of the microscopic cell images characteristic and the shortcomings of the traditional segmentation algorithm. Through theoretical analysis and contrast test, the segmentation method proposed is superior to the traditional threshold segmentation method in microscopic cell images, and the average segmentation time o

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Mo, Shu, and Xiao Dong Yang. "A Color Image Enhancement Based on Improved Genetic Algorithm." Applied Mechanics and Materials 475-476 (December 2013): 342–46. http://dx.doi.org/10.4028/www.scientific.net/amm.475-476.342.

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Image enhancement plays a fundamental role in image processing. Because of the influence of internal and external factors such as the sensor precision,light,random noise.It has a certain difficulty for image recognition directly.To solve such problems, we proposed a novel and efficient enhancement method based on improved genetic algorithm. This paper combined median filter and improved genetic algorithm to enhance the visual effect of color image. Simulation results proved that the proposed method was stronger than traditional method in terms of details and contrast enhancement and natural vi

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Roy, Abhisek, Roy Pranab Kanti, Anirban Mitra, et al. "Artificial bee colony-based nonrigid demons registration." Artificial bee colony-based nonrigid demons registration 14, no. 4 (2024): 3951–61. https://doi.org/10.11591/ijece.v14i4.pp3951-3961.

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The artificial bee colony (ABC) algorithm has gained popularity in recent years for its ability to solve optimization problems. The accuracy and resilience of ABC-based image processing techniques have demonstrated encouraging outcomes. The ABC method is an excellent solution for image processing issues since it has the ability to swiftly and effectively explore the search space. The current research intends to address image registration issues by refining the existing image registration strategy using ABC algorithm. The process of nonrigid demons registratio

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Ali, Alzahrani, and Al-Amin Bhuiyan Md. "Feature selection for urban land cover classification employing genetic algorithm." Bulletin of Electrical Engineering and Informatics 11, no. 2 (2022): 793–802. https://doi.org/10.11591/eei.v11i2.3399.

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Feature selection has attained substantial research interest in image processing, computer vision, pattern recognition and so on due to tremendous dimensional reduction in image analysis. This research addresses a genetic algorithm based feature selection strategy for urban land cover classification. The principal purpose of this research is to monitor the land cover alterations in satellite imagery for urban planning. The method is based on object based classification by detecting the object area of a given image with the knowledge of visual information of the object from remote sensing image

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Yang, Chen-Hsien, and Jih-Gau Juang. "Guide Robot Based on Image Processing and Path Planning." Machines 13, no. 7 (2025): 560. https://doi.org/10.3390/machines13070560.

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While guide dogs remain the primary aid for visually impaired individuals, robotic guides continue to be an important area of research. This study introduces an indoor guide robot designed to physically assist a blind person by holding their hand with a robotic arm and guiding them to a specified destination. To enable hand-holding, we employed a camera combined with object detection to identify the human hand and a closed-loop control system to manage the robotic arm’s movements. For path planning, we implemented a Dueling Double Deep Q Network (D3QN) enhanced with a genetic algorithm. To add

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