Research on visual recognition and localization based on K-means and OTSU

This paper proposes a visual recognition and localization method based on color classification by K-means and OTSU. Based on the characteristics of HSV color space which is convenient for color segmentation, after transferring the image from RGB color space to HSV color space, the K-means algorithm is combined with the difference method to segment the targets with the same color characteristics. For the targets with the same color characteristics, the OTSU algorithm is considered to segment the top surface of the target in the S-channel of the image, and the center of the top surface of the target is calculated using the image processing method as the suction point of the robotic handling. The experimental results show that the method is characterized by high accuracy, robustness and real-time performance in experiments such as target recognition based on color classification.