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In order to solve problems relating to online recognition of stems/calyxes and bruise of apples, a selfdesigned machine vision inspection system was applied to online image acquisition of apples, images of three different motion states were synthesized by the automatic segmentation synthesis algorithm, and stems/calyxes and bruise in images of apples were extracted by the areaofinterest extraction algorithm. To study applicability of different characteristics of images, early bruise midterm bruise and later bruise were identified through variables of textural features and edge gradient features respectively. As textures of stems and calyxes were more complex than those of early and middle bruise, the support vector machine model based on two variables of textural features, namely entropy and energy/angular second moment, was used and showed a good effect with an overall accuracy of 97%. Due to brown stain and depression of the most later bruises, its textural characteristics were similar to those of stems and calyxes. Hence, later bruise can not be distinguished from stems and calyxes with parameters of textural characteristics. As a result, an edge gradient features extraction algorithm was designed to extract peak intensity and peak positions of later bruises, stems and calyxes and a support vector machine model was created with an overall accuracy of 96%. On this basis, a comprehensive inspection algorithm about stems/calyxes and bruise of apples was designed. Totally 80 different types of bruiserelated algorithms were purchased to verify this algorithm and its accuracy reached 95%. Testing results showed that online recognition of stems/calyxes and bruise of apples could be realized through this algorithm.