The Apple Recognition based on Support Vector Machine Using in Apple Harvesting Robot

In the robot vision system of the apple harvesting robot, the key is to recognize and locate the apple. To solve recognition questions such as high error rate, too much calculation and time consuming, a new recognizing method, Support Vector Machine (SVM) is applied to improve recognition accuracy and efficiency. Segmentation of the images based on seeded region growing method and color properties is done. Color properties and shape properties are extracted for the recognition of apple images based on SVM. Experimental results indicate that the classification performance of SVM is better than that of neural networks. The RBF SVM function based on color and shape properties is the best for apple recognition.