윤곽선 방향의 히스토그램과 Sampled Spot Matching을 이용한 이치 형상의 인식 알고리즘

A Study on the Recognition of Bilevel Shapes Using the Contour Direction Histogram & Spot Matching Method

Pattern Recognition is one of the fundamental areas of computer vision. The recognition of patterns with varying size and severe defects is especially important. However, it is known that the conventional algorithms such as GHT or structural approaches have limitations in speed and accuracy. In this paper, in order to avoid above-mentioned problems, we propose a new recognition algorithm which exploits the histogram of contour directions and the sampled spot matching method. While the former provides little influence against size variation, the latter has strong immunity to noise and defects. We applied those proposed algorithms for the recognition of numbers extracted from the car number plates and shapes of aircraft. Experimental result shows that it is possible to solve above-mentioned problems by complementary uses of those two suggested algorithms. The contour directional histogram method resulted in high-speed of average 0.013 sec/char and 0.1 sec/aircraft-image on IBM-386. The accuracy of recognition is as high as 99%. Sampled spot matching method has less speed than the former one, however, it showed fairly strong immunity to noise and defects.