The extraction algorithm of color disease spot image based on Otsu and watershed

In this paper, an extraction algorithm of color disease spot image based on Otsu and watershed is proposed to overcome the problem of excessive segmentation in the traditional watershed algorithm. The proposed algorithm converts the color space of the color spot image to calculate the component gradient that is not interfered by the reflected light in the new color space. Then, final gradient image is obtained from the gradient image reconstructed by open and close operation under the different-sized structural elements. The label from the final gradient image is extracted by Otsu algorithm, and then, the H-minima transform is used to modify the labeled image. The modified gradient image is transformed with a label by the watershed algorithm. Finally, the extraction of the disease spot is implemented. The experimental results show that the proposed approach obtains accurate and continuous target contour and reaches the requirement of human visual characteristics. Compared with other similar algorithms, the proposed algorithm can effectively suppress the impact of reflected light, optimize the extraction results of disease spot, better maintain the information of disease spot image, and improve the robustness and the applicability.