The defects, size, color of fruit and the lighting influence the accuracy of segmentation. In order to improve the segmentation accuracy, a combinational method was presented based on apple images processing. The R, G, B components were calculated by arithmetic operations at first. Then the arithmetic result was processed for noise cancellation by morphological opening and for smooth boundary by linear spatial filtering. After these operations, the automatic threshold method was used for background segmentation. This combinational method shows good performance to process 280 images of apples with different attitudes, size, color and defects. And these images were gained in 4 types of illumination conditions. The segmentation deviations of 203 images which are 72.5% of total images are less than 1%. The segmentation deviations of 70 images which are 25% of total images are larger than 1% but less than 2%. Only 7 images’ deviations are larger than 2%, and the maximum segmentation deviation is 2.83%.