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Optical Engineering

Three-dimensional shape enhanced transform for automatic apple stem-end/calyx identification
Author(s): Bin Zhu; Lu Jiang; Yang Tao
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Paper 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.

Paper Details

Date Published: 1 January 2007
PDF: 9 pages
Opt. Eng. 46(1) 017201 doi: 10.1117/1.2434382
Published in: Optical Engineering Volume 46, Issue 1
Show Author Affiliations
Bin Zhu, Univ. of Maryland/College Park (United States)
Lu Jiang, Univ. of Maryland/College Park (United States)
Yang Tao, Univ. of Maryland/College Park (United States)

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