An apple recognition method based on color space

With the development of agricultural intelligence, robots replacing manual labor in agricultural production has become an inevitable trend. For apple picking robots, accurate identification of apples is the primary step in their work. At present, the existing L*a*b and OHTA color spaces have problems of incomplete extraction of apple regions and incomplete differentiation of fruit and leaves. To address this issue, this study designed a color space (LPX color space) specifically for apple recognition, and based on this, proposed a complete algorithm for identifying green or red apples in a complex open environment. The experimental results show that the algorithm has high recognition accuracy in both cases of apples being shaded and unshaded, and can provide accurate orientation for the subsequent automated apple picking.