Kim Kwan Dong, Lee Ji Yong, Lee Byeng Gon, Ahn Jae Hyeong

The Transactions of the Korea Information Processing Society (1994 ~ 2000), Vol. 5, No. 7, pp. 1923-1932, Jul. 1998
10.3745/KIPSTE.1998.5.7.1923,   PDF Download:

Abstract

This paper deals with a 2-D objects recognition algorithm. And in this paper, we present an algorithm which can reduce the computation time in model retrieval by means of hashing technique instead of using the binary-tree method. In this paper, we treat an object boundary as a string of structural units and use an attributed string matching algorithm to compute similarity measure between two strings. We select from the privileged strings a privileged string with minimal eccentricity. This privileged string is treated as the reference string. And then we constructed hash table using the distance between privileged string and the reference string as a key value. Once the database of all model strings is built, the recognition proceeds by segmenting the scene into a polygonal approximation. The distance between privileged string extracted from the scene and the reference string is used for model hypothesis retrieval from the table. As a result of the computer simulation, the proposed method can recognize objects only computing the distance 2-3 times, while previous method should compute the distance 8-10 times for model retrieval.

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