Segmentation of scanned insect footprints using ART2 for threshold selection

Authors:
Bok-Suk Shin;Eui-Young Cha;Young Woon Woo;Reinhard Klette
Affiliations:
Dept. of Computer Science, Pusan National University, Busan, Korea;Dept. of Computer Science, Pusan National University, Busan, Korea;Dept. of Multimedia Engineering, Dong-Eui University, Busan, Korea;Dept. of Computer Science, The University of Auckland, Auckland, New Zealand
Venue:
PSIVT'07 Proceedings of the 2nd Pacific Rim conference on Advances in image and video technology
Year:
2007

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Abstract

In a process of insect footprint recognition, footprint segments need to be extracted from scanned insect footprints in order to find out appropriate features for classification. In this paper, we use a clustering method in a preprocessing stage for extraction of insect footprint segments. In general, sizes and strides of footprints may be different according to type and size of an insect for recognition. Therefore we propose a method for insect footprint segment extraction using an improved ART2 algorithm regardless of size and stride of footprint pattern. In the improved ART2 algorithm, an initial threshold value for clustering is determined automatically using the contour shape of the graph created by accumulating distances between all the spots within a binarized footprint pattern image. In the experimental results, applying the proposed method to two kinds of insect footprint patterns, we illustrate that clustering is accomplished correctly.