Log in

Relevant bibliographies by topics / Genetic Algorithm and Image Processing

Contents

Journal articles
Dissertations / Theses
Books
Book chapters
Conference papers
Reports

Academic literature on the topic 'Genetic Algorithm and Image Processing'

Author: Grafiati

Published: 3 June 2025

Last updated: 19 July 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Genetic Algorithm and Image Processing.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

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

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.

Full text

Abstract:

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

APA, Harvard, Vancouver, ISO, and other styles

2

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.

Full text

Abstract:

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

APA, Harvard, Vancouver, ISO, and other styles

3

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.

Full text

Abstract:

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

APA, Harvard, Vancouver, ISO, and other styles

4

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.

Full text

Abstract:

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

APA, Harvard, Vancouver, ISO, and other styles

5

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.

Full text

Abstract:

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

APA, Harvard, Vancouver, ISO, and other styles

6

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.

Full text

Abstract:

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

APA, Harvard, Vancouver, ISO, and other styles

7

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.

Full text

Abstract:

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

APA, Harvard, Vancouver, ISO, and other styles

8

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.

Full text

Abstract:

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

APA, Harvard, Vancouver, ISO, and other styles

9

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.

Full text

Abstract:

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.

APA, Harvard, Vancouver, ISO, and other styles

10

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.

Full text

Abstract:

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

APA, Harvard, Vancouver, ISO, and other styles

More sources

Dissertations / Theses on the topic "Genetic Algorithm and Image Processing"

1

Murnion, Shane D. "Neural and genetic algorithm applications in GIS and remote sensing." Thesis, Queen's University Belfast, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.337024.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Yu, Xinren. "Pavement Surface Distress Detection and Evaluation Using Image Processing Technology." University of Toledo / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1302032254.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Uren, PJ. "Investigation of Distributed and Parallel Performance of a Genetic Algorithm." Thesis, Honours thesis, University of Tasmania, 2004. https://eprints.utas.edu.au/101/1/Philip_Uren_Thesis_Final.pdf.

Full text

Abstract:

Genetic algorithms, a stochastic evolutionary computing technique, have demonstrated a capacity for robust, efficient problem solving through highly parallel search space exploration. This work demonstrates how an improvement in performance and efficiency over the traditional serial approach can be achieved by exploiting this highly parallel nature to produce parallel genetic algorithms. Furthermore, it is shown that by incorporating domain specific knowledge into a genetic algorithm near optimal solutions can be located in minimal time.

APA, Harvard, Vancouver, ISO, and other styles

4

Chapagain, Prerak. "Optimization Techniques for Image Processing." ScholarWorks@UNO, 2019. https://scholarworks.uno.edu/honors_theses/133.

Full text

Abstract:

This research thesis starts off with a basic introduction to optimization and image processing. Because there are several different tools to apply optimization in image processing applications, we started researching one category of mathematical optimization techniques, namely Convex Optimization. This thesis provides a basic background consisting of mathematical concepts, as well as some challenges of employing Convex Optimization in solving problems. One major issue is to be able to identify the convexity of the problem in a potential application (Boyd). After spending a couple of months res

APA, Harvard, Vancouver, ISO, and other styles

5

Tsai, Ya-Lin. "Development of parallel processing algorithms to provide automatic image analysis for medical application." Thesis, University of Sunderland, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.336914.

Full text

Abstract:

This thesis describes the development of: (i) an automatic chromosome analysis system capable of producing to a high degree of accuracy and consistency a correct classification for damaged chromosomes at a low cost and (ii) a parallel computer system to enable more rapid chromosome analysis. Chromosomes can be examined in a cytogenetics laboratory for a variety of purposes including an assessment of the affects of ionisation exposure on the genetic code of the cell. Scoring of chromosome aberrations caused by ionisation of radiation exposure, is possible by detecting dicentric chromosomes. In

APA, Harvard, Vancouver, ISO, and other styles

6

Hobbs, Mike. "Genetic algorithms for spatial data analysis in geographical information systems." Thesis, University of Kent, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.262636.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Egan, Thomas Michael. "An investigation into the use of genetic algorithms for shape recognition." Thesis, Open University, 1998. http://oro.open.ac.uk/57748/.

Full text

Abstract:

The use of the genetic algorithm for shape recognition has been investigated in relation to features along a shape boundary contour. Various methods for encoding chromosomes were investigated, the most successful of which led to the development of a new technique to input normalised 'perceptually important point' features from the contour into a genetic algorithm. Chromosomes evolve with genes defining various ways of 'observing' different parts of the contour. The normalisation process provides the capability for multi-scale spatial frequency filtering and fine/coarse resolution of the contou

APA, Harvard, Vancouver, ISO, and other styles

8

Gadde, Pramod. "AFFINE IMAGE REGISTRATION USING ARTIFICIAL NEURAL NETWORKS." DigitalCommons@CalPoly, 2013. https://digitalcommons.calpoly.edu/theses/982.

Full text

Abstract:

This thesis deals with image registration of MRI images using neural networks. Image registration combines multiple images of the same subject that were taken at different points in time, from different sensors, or from different points of views into a single image and coordinate system. Image registration is widely used in medical imaging and remote sensing. In this thesis feed forward neural networks and wavelet neural networks are used to estimate the parameters of registration. Simulations show that the wavelet networks provide significantly more accurate results than feed forward networks

APA, Harvard, Vancouver, ISO, and other styles

9

Komjáthy, Gergely. "Koevoluce obrazových filtrů a detektorů šumu." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2014. http://www.nusl.cz/ntk/nusl-412903.

Full text

Abstract:

This thesis deals with image filter design using coevolutionary algorithms. It contains a description of evolutionary algorithms, focusing on genetic programming, cartesian genetic programming and coevolution, the reader can learn about image filters too. The next chapters contain the design of image filters and noise detectors using cooperative coevolution, and the implementation and testing of the proposed filter. In the last chapter the proposed filter is compared to other filters created using evolutionary algorithms but without coevolution.

APA, Harvard, Vancouver, ISO, and other styles

10

Muttayane, Anandajothi. "Towards Colour Imaging with the Image Ranger." The University of Waikato, 2006. http://hdl.handle.net/10289/2388.

Full text

Abstract:

Many of the colour images captured by different types of digital camera do not provide quality colour image according to human visual perception. In this study we explore technique for colour correction of the colour images from the Waikato Image Ranger. Colour images were captured using three different illuminants with the Waikato Image Ranger. The colour image formed from the ranger data do not have good quality because illuminants used do not match usual RGB standard illuminants. The spectral power distribution values of the illuminants were measured using spectroradiometer. To calculate tr

APA, Harvard, Vancouver, ISO, and other styles

More sources

Books on the topic "Genetic Algorithm and Image Processing"

1

Mars, P. Learning algorithms: Theory and applications in signal processing, control, and communications. CRC Press, 1996.

Find full text

APA, Harvard, Vancouver, ISO, and other styles

2

Gogniat, Guy, Dragomir Milojevic, Adam Morawiec, and Ahmet Erdogan, eds. Algorithm-Architecture Matching for Signal and Image Processing. Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-90-481-9965-5.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Karr, C. L. Genetic algorithm applied to least squares curve fitting. U.S. Dept. of the Interior, Bureau of Mines, 1990.

Find full text

APA, Harvard, Vancouver, ISO, and other styles

4

Bhanu, Bir. Genetic learning for adaptive image segmentation. Kluwer Academic Publishers, 1994.

Find full text

APA, Harvard, Vancouver, ISO, and other styles

5

Moayeri, Nader. An algorithm for blind restoration of blurred and noisy images. Hewlett-Packard Laboratories, Technical Publications Department, 1996.

Find full text

APA, Harvard, Vancouver, ISO, and other styles

6

P, DeFigueiredo Rui J., Krishen Kumar, and United States. National Aeronautics and Space Administration., eds. Formulation and error analysis for a generalized image point correspondence algorithm. Academic Press, Inc., 1992.

Find full text

APA, Harvard, Vancouver, ISO, and other styles

7

P, DeFigueiredo Rui J., Krishen Kumar, and United States. National Aeronautics and Space Administration., eds. Formulation and error analysis for a generalized image point correspondence algorithm. Academic Press, Inc., 1992.

Find full text

APA, Harvard, Vancouver, ISO, and other styles

8

Cagnoni, Stefano, E. velyne Lutton, and Gustavo Olague. Genetic and evolutionary computation for image processing and analysis. Hindawi Publishing Corporation, 2008.

Find full text

APA, Harvard, Vancouver, ISO, and other styles

9

Ventura, Roberto M. Analysis of an image processing algorithm for its implementation in real time. Naval Postgraduate School, 1988.

Find full text

APA, Harvard, Vancouver, ISO, and other styles

10

Zidong, Wang, and Liu Xiaohui, eds. Microarray image analysis: An algorithmic approach. Chapman & Hall/CRC, 2010.

Find full text

APA, Harvard, Vancouver, ISO, and other styles

More sources

Book chapters on the topic "Genetic Algorithm and Image Processing"

1

Shioyama, Tadayoshi, Akira Okumura, and Yoshikazu Aoki. "Genetic algorithm for thinning gray-scale images of characters." In Image Analysis and Processing. Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/3-540-60298-4_315.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Kim, Ho-Chan, Chang-Jin Boo, and Min-Jae Kang. "Image Reconstruction Using Genetic Algorithm in Electrical Impedance Tomography." In Neural Information Processing. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11893295_103.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Dutta, Tulika, Sandip Dey, Siddhartha Bhattacharyya, and Somnath Mukhopadhyay. "Qutrit-Based Genetic Algorithm for Hyperspectral Image Thresholding." In Recent Trends in Signal and Image Processing. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6966-5_3.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Mitra, Suman K., C. A. Murthy, and M. K. Kundu. "Image Compression and Edge Extraction Using Fractal Technique and Genetic Algorithm." In Soft Computing for Image Processing. Physica-Verlag HD, 2000. http://dx.doi.org/10.1007/978-3-7908-1858-1_4.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Andrade, Aniceto C., Zenilton K. G. Patrocínio, and Silvio Jamil F. Guimarães. "Improving the Quality of Color Image Segmentation Using Genetic Algorithm." In Image Analysis and Processing – ICIAP 2013. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41181-6_16.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Pathangay, Vinod, and Sukhendu Das. "Selection of Wavelet Subbands Using Genetic Algorithm for Face Recognition." In Computer Vision, Graphics and Image Processing. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11949619_52.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Munteanu, Cristian, and Vasile Lazarescu. "Improving Mutation Capabilities in a Real-Coded Genetic Algorithm." In Evolutionary Image Analysis, Signal Processing and Telecommunications. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/10704703_11.

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

Maity, Santi P., Malay K. Kundu, and Prasanta K. Nandi. "Genetic Algorithm for Optimal Imperceptibility in Image Communication Through Noisy Channel." In Neural Information Processing. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30499-9_107.

Full text

APA, Harvard, Vancouver, ISO, and other styles

9

He, Lifeng, Yuyan Chao, Tsuyoshi Nakamura, and Hidenori Itoh. "Genetic Algorithm and Fuzzy Reasoning for Digital Image Compression Using Triangular Plane Patches." In Soft Computing for Image Processing. Physica-Verlag HD, 2000. http://dx.doi.org/10.1007/978-3-7908-1858-1_8.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Webb, Andrew, Brian Turton, and John Brown. "A Genetic Algorithm for Designing Networks with Desirable Topological Properties." In Evolutionary Image Analysis, Signal Processing and Telecommunications. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/10704703_14.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Genetic Algorithm and Image Processing"

1

Yuan, Meishi, Zhiduo Diao, Xiaohui He, Li Yang, Haiming Sun, and Hao Yu. "Image processing of solid wood panels based on genetic algorithm." In 2024 International Conference on Electronics and Devices, Computational Science (ICEDCS). IEEE, 2024. https://doi.org/10.1109/icedcs64328.2024.00082.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Zhao, Qun, and Yuan-Gen Wang. "Universal Black-Box Adversarial Patch Attack with Optimized Genetic Algorithm." In 2024 IEEE International Conference on Image Processing (ICIP). IEEE, 2024. http://dx.doi.org/10.1109/icip51287.2024.10647345.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Xia, Xiaoxiang. "Research on Improving Genetic Algorithm in Mobile Robot Path Planning." In 2024 2nd International Conference on Algorithm, Image Processing and Machine Vision (AIPMV). IEEE, 2024. http://dx.doi.org/10.1109/aipmv62663.2024.10692004.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Kim, In K., and Rae-Hong Park. "Block matching algorithm using a genetic algorithm." In Visual Communications and Image Processing '95, edited by Lance T. Wu. SPIE, 1995. http://dx.doi.org/10.1117/12.206690.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Yi, Min, Mingyue Ding, and Chengping Zhou. "3D route planning using genetic algorithm." In International Symposium on Multispectral Image Processing, edited by Ji Zhou, Anil K. Jain, Tianxu Zhang, Yaoting Zhu, Mingyue Ding, and Jianguo Liu. SPIE, 1998. http://dx.doi.org/10.1117/12.323573.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Afarin, Roza, and Saeed Mozaffari. "Image encryption using genetic algorithm." In 2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP). IEEE, 2013. http://dx.doi.org/10.1109/iranianmvip.2013.6780026.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Jennane, R., A. Almhdie-Imjabber, R. Hambli, O. N. Ucan, and C. L. Benhamou. "Genetic algorithm and image processing for osteoporosis diagnosis." In 2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2010). IEEE, 2010. http://dx.doi.org/10.1109/iembs.2010.5626804.

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

Jayasinghe, J. P. B. A., and A. M. R. R. Bandara. "Finding Feasible Image Processing Pipeline Using Genetic Algorithm." In 2021 21st International Conference on Advances in ICT for Emerging Regions (ICter). IEEE, 2021. http://dx.doi.org/10.1109/icter53630.2021.9774817.

Full text

APA, Harvard, Vancouver, ISO, and other styles

9

Momeni, Milad, Zahra Hossieni Nezhad, and Mohsen Ebrahimi Moghaddam. "Embryonic image enhancement based on genetic algorithm and generic filter." In 2017 3rd International Conference on Frontiers of Signal Processing (ICFSP). IEEE, 2017. http://dx.doi.org/10.1109/icfsp.2017.8097158.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Li, Yurong, and Jingping Jiang. "New algorithm for combining classifiers based on fuzzy integral and genetic algorithms." In Multispectral Image Processing and Pattern Recognition, edited by Jun Shen, Sharatchandra Pankanti, and Runsheng Wang. SPIE, 2001. http://dx.doi.org/10.1117/12.441640.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Reports on the topic "Genetic Algorithm and Image Processing"

1

Ghosh, Payel. Medical Image Segmentation Using a Genetic Algorithm. Portland State University Library, 2000. http://dx.doi.org/10.15760/etd.25.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Fedkiw, Ron. Algorithm Design for Computational Fluid Dynamics, Scientific Visualization, and Image Processing. Defense Technical Information Center, 2007. http://dx.doi.org/10.21236/ada461529.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Sun, Xiaobai, and Nikos P. Pitsianis. FANTOM: Algorithm-Architecture Codesign for High-Performance Embedded Signal and Image Processing Systems. Defense Technical Information Center, 2013. http://dx.doi.org/10.21236/ada581464.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Asari, Vijayan, Paheding Sidike, Binu Nair, Saibabu Arigela, Varun Santhaseelan, and Chen Cui. PR-433-133700-R01 Pipeline Right-of-Way Automated Threat Detection by Advanced Image Analysis. Pipeline Research Council International, Inc. (PRCI), 2015. http://dx.doi.org/10.55274/r0010891.

Full text

Abstract:

A novel algorithmic framework for the robust detection and classification of machinery threats and other potentially harmful objects intruding onto a pipeline right-of-way (ROW) is designed from three perspectives: visibility improvement, context-based segmentation, and object recognition/classification. In the first part of the framework, an adaptive image enhancement algorithm is utilized to improve the visibility of aerial imagery to aid in threat detection. In this technique, a nonlinear transfer function is developed to enhance the processing of aerial imagery with extremely non-uniform l

APA, Harvard, Vancouver, ISO, and other styles

5

O'Neill, Francis, Kristofer Lasko, and Elena Sava. Snow-covered region improvements to a support vector machine-based semi-automated land cover mapping decision support tool. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/45842.

Full text

Abstract:

This work builds on the original semi-automated land cover mapping algorithm and quantifies improvements to class accuracy, analyzes the results, and conducts a more in-depth accuracy assessment in conjunction with test sites and the National Land Cover Database (NLCD). This algorithm uses support vector machines trained on data collected across the continental United States to generate a pre-trained model for inclusion into a decision support tool within ArcGIS Pro. Version 2 includes an additional snow cover class and accounts for snow cover effects within the other land cover classes. Overa

APA, Harvard, Vancouver, ISO, and other styles

6

Anderson, Gerald L., and Kalman Peleg. Precision Cropping by Remotely Sensed Prorotype Plots and Calibration in the Complex Domain. United States Department of Agriculture, 2002. http://dx.doi.org/10.32747/2002.7585193.bard.

Full text

Abstract:

This research report describes a methodology whereby multi-spectral and hyperspectral imagery from remote sensing, is used for deriving predicted field maps of selected plant growth attributes which are required for precision cropping. A major task in precision cropping is to establish areas of the field that differ from the rest of the field and share a common characteristic. Yield distribution f maps can be prepared by yield monitors, which are available for some harvester types. Other field attributes of interest in precision cropping, e.g. soil properties, leaf Nitrate, biomass etc. are ob

APA, Harvard, Vancouver, ISO, and other styles

7

Lee, W. S., Victor Alchanatis, and Asher Levi. Innovative yield mapping system using hyperspectral and thermal imaging for precision tree crop management. United States Department of Agriculture, 2014. http://dx.doi.org/10.32747/2014.7598158.bard.

Full text

Abstract:

Original objectives and revisions – The original overall objective was to develop, test and validate a prototype yield mapping system for unit area to increase yield and profit for tree crops. Specific objectives were: (1) to develop a yield mapping system for a static situation, using hyperspectral and thermal imaging independently, (2) to integrate hyperspectral and thermal imaging for improved yield estimation by combining thermal images with hyperspectral images to improve fruit detection, and (3) to expand the system to a mobile platform for a stop-measure- and-go situation. There were no

APA, Harvard, Vancouver, ISO, and other styles

8

Engel, Bernard, Yael Edan, James Simon, Hanoch Pasternak, and Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, 1996. http://dx.doi.org/10.32747/1996.7613033.bard.

Full text

Abstract:

The objectives of this project were to develop procedures and models, based on neural networks, for quality sorting of agricultural produce. Two research teams, one in Purdue University and the other in Israel, coordinated their research efforts on different aspects of each objective utilizing both melons and tomatoes as case studies. At Purdue: An expert system was developed to measure variances in human grading. Data were acquired from eight sensors: vision, two firmness sensors (destructive and nondestructive), chlorophyll from fluorescence, color sensor, electronic sniffer for odor detecti

APA, Harvard, Vancouver, ISO, and other styles

9

Searcy, Stephen W., and Kalman Peleg. Adaptive Sorting of Fresh Produce. United States Department of Agriculture, 1993. http://dx.doi.org/10.32747/1993.7568747.bard.

Full text

Abstract:

This project includes two main parts: Development of a “Selective Wavelength Imaging Sensor” and an “Adaptive Classifiery System” for adaptive imaging and sorting of agricultural products respectively. Three different technologies were investigated for building a selectable wavelength imaging sensor: diffraction gratings, tunable filters and linear variable filters. Each technology was analyzed and evaluated as the basis for implementing the adaptive sensor. Acousto optic tunable filters were found to be most suitable for the selective wavelength imaging sensor. Consequently, a selectable wave

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!