In view of actual situations such as light change, soil, branch and leaf background and fruit overlap in the natural environment, which causing the problem of red tomato recognition during the robotic picking process was not accurate, a tomato image recognition method based on circle fitting algorithm was proposed. We collected the images of tomato by camera, used the red, green, blue (RGB) color space based Matlab as simulation experiment, and preprocessed the tomato images with red-green (R-G) color component. Then, edge detection algorithm, threshold segmentation and watershed segmentation methods were adopted to segment tomato target and the background, respectively. The Otsu segmentation method of threshold segmentation was adopted, which was best to segment target. We used the back propagation-artificial neural network (BP-ANN) and circle fitting algorithm to recognize the tomato fruit. Finally, the contour, centroid and radius of the red tomato were obtained. The results of red tomato images were statistically analyzed, and the recognition rate of circle fitting algorithm was as high as 90.07%. This algorithm not only has a high recognition rate for single fruit, but also solves the problem of multiple fruit overlapping in a complex environment, which lays a good foundation for the following robotic picking work.