Atomic Potential Matching: An Evolutionary Target Recognition Approach Based on Edge Features
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% To start the optimization, run the M file named "run_me.m".
% To depict the simulation results, functions "result_illustration.m" and "multi_plotting_process.m" will be useful.
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% To have a quick look of the optimized results, function "Run_demo.m" will be useful.
% - test_image.bmp should be prepared as the image to be tested.
% - target_contour,bmp contains the target shape.
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% If there is any question, feel free to contact me via libai@zju.edu.cn or directly, libaioutstanding@163.com
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Cite As
Li Bai (2024). Atomic Potential Matching: An Evolutionary Target Recognition Approach Based on Edge Features (https://www.mathworks.com/matlabcentral/fileexchange/54502-atomic-potential-matching-an-evolutionary-target-recognition-approach-based-on-edge-features), MATLAB Central File Exchange. Retrieved .
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- Image Processing and Computer Vision > Image Processing Toolbox > Image Segmentation and Analysis > Object Analysis >
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