step1: make a standardized template library (all fruit, 51x51).
step2: extract an individual object from an image and generate a single line edge (contour).
step3: standardize the image (normalized, single line, 51x51).
step4: use the central point as fix point, clockwise scan the two template images (contour projection).
step5: choose a tolerance value (3 or 5 pixels) to evaluate the image with each template, and get a score (contour matching).
step6: decide what kind of fruit it is by lowest score.
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Hi, I am professional in fruit recognition. I am very familiar with deciding what kind of fruit it is by lowest score. I can help you with high quality. Thanks.