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5 July 1995 Study on object recognition using morphological shape decomposition
Kyoung-Bae Eum, Joon-Cheol Kim, Joon-Whoan Lee
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Proceedings Volume 2485, Automatic Object Recognition V; (1995) https://doi.org/10.1117/12.213100
Event: SPIE's 1995 Symposium on OE/Aerospace Sensing and Dual Use Photonics, 1995, Orlando, FL, United States
Abstract
Mathematical morphology based on set theory has been applied to various areas in image processing. Pita proposed an object recognition algorithm using morphological shape representation (MSR). The MSR is a representation scheme to combine constructive solid geometry and MSD. Pita's algorithm is a simple and adequate approach to recognize objects that are rotated 45 degree-units with respect to the model object. However, this recognition scheme fails in the case of random rotation. This disadvantage may be compensated by defining small angle increments. However, this solution may greatly increase computational complexity because the smaller the step, more number of rotations needed. In this paper, we propose a new method for object recognition based on MSD. The first step of our method decomposes a binary shape into a union of simple binary shapes, and then a new tree structure is constructed which can represent the relations of binary shapes in an object. Finally, we obtain the feature information invariant to the rotation, translation, and scaling from the tree, and calculate matching scores using efficient matching measure. Because our method does not need to rotate the object to be tested, it could be more efficient than Pita's method. MSR has an intricate structure so that it might be difficult to calculate matching scores even for a little complex object. But our tree has a simpler structure than MSR, and it is easier to calculate the matching score. We experimented on 20 test images, and scaled, rotated, and translated versions of five kinds of automobile images. The simulation result using octagonal structure elements shows 95% recognition rate. The experimental results using approximated circular structure elements are examined. ALso, the effect of noise on MSR scheme is discussed.
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Kyoung-Bae Eum, Joon-Cheol Kim, and Joon-Whoan Lee "Study on object recognition using morphological shape decomposition", Proc. SPIE 2485, Automatic Object Recognition V, (5 July 1995); https://doi.org/10.1117/12.213100
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KEYWORDS
Object recognition
Binary data
Chemical elements
Detection and tracking algorithms
Data modeling
Mathematical morphology
Image processing
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