自己相関関数のグラフの形を利用した商標図形の分類

概要

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The auto-correlation function graph figure considerably represents characteristics of image figures and outline shapes. This paper presents a method for classifying registered trademark images according to a function which has been made of the auto-correlation function. Most of registered trademark images are formed with a couple of outer figure or frame and inner figures or characters. Due to this, image figure patterns and the number of pixels have influence on the auto-correlation function for image patterns and its graph figure can be separated into three domains where each figure shows quite different characteristic. Considering the characteristic on each domain, the auto-correlation function can be exchanged into a set of three piecewise expressions: an exponential, a sign, and a third order polynomial expression. This transformed function is defined as the similar function in this paper. The point of this function is whether its graph figure is similar to the original auto-correlation graph figure. Experimental results with 1103 registered trademark images have shown that the proposed method has conducted the same classification as image classification by 20 people at a rate of 93.7%.
社団法人電気学会の論文
2003-09-01