1 January 2007 Three-dimensional shape enhanced transform for automatic apple stem-end/calyx identification
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Abstract
In automated apple sorting and grading applications, one persistent problem is to identify apple stem-ends and calyxes from defects. To solve this problem, a Three-dimensional (3D) Shape Enhanced Transform (SET) approach is presented. The SET method enhances the apple stem-end/calyx area according to the 3D surface gradient difference between the stem-end/calyx and the apple surface region. In addition, the proposed SET approach does not depend on the location of the stem-end/calyx on the apple surface, making it more suitable for apples orientated randomly. SET is also an automated and robust method, which detects the apple stem-end/calyx without any human intervention, and performs well with noise and even incomplete image data. A total of 232 Golden Delicious apple images were tested, and an overall detection rate of 93.97% was achieved.
© (2007) Society of Photo-Optical Instrumentation Engineers (SPIE)
Bin Zhu, Lu Jiang, Yang Tao, "Three-dimensional shape enhanced transform for automatic apple stem-end/calyx identification," Optical Engineering 46(1), 017201 (1 January 2007). https://doi.org/10.1117/1.2434382 . Submission:
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