Object contour extraction based on merging photometric information with graph cuts

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Abstract

Graph cuts algorithm is one of high effective optimal methods in image segmentations. To improve the effect of segmentation caused by uneven illumination, a contour extraction method which merges photometric information with graph cuts is proposed. Firstly, the method gets the color values and brightness values of pixel depending on the color image, represents photometric values with the average of these values. Then, the photometric information is integrated into the energy function of active contour model, and a new energy function is built. Finally, we can get the optimal solution for solving new energy function with max-flow/min-cut algorithm, obtain global and local contours of the target object. Experimental results show that the proposed method can make initial contour convergence to the target object more accurately and faster.

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Zhang, R., Ren, M., Hu, J., Liu, X., & Liu, K. (2015). Object contour extraction based on merging photometric information with graph cuts. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9218, pp. 584–599). Springer Verlag. https://doi.org/10.1007/978-3-319-21963-9_54

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