抄録
This paper deals with a methodology and a system of the profile pattern recognition of a motorcar. The pattern is assumed to be a polygon constructed by simplifying a complicated shape pattern. In the methodology of the motorcar shape recognition, six kinds of parameters of feature extraction are adopted such as the numcer of corners, the number of separated concave corners, the number of continuous concave corners, the aspect ratio, the maximum edge ratio and the size of the pattern.
Furthermore, it is proposed to apply the operation of simplifying the pattern when the complicated shape pattern such as a motorcar shape is subjected to the pattern recognition. An analysis of human being in the complicated shape pattern recognition has been executed and the experimental results showed two characteristic features of simplification. One is a character which simplifies a corner with respect to a corner angle. Another is a character with respect to a distance between adjacent corners. The stress of each corner is defined from these two characteristic features. If the stress of each corner is smaller than the given threshold stress value, the corner is simplified and neglected.
Seven kinds of grouping patterns which are symbolized referring to the sectional profile pattern of a motorcar commonly encountered in the road are considered. The sectional profile pattern is selected as a side pattern of the motorcar. The grouping patterns are a bus, a micro-bus, a large-truck, a truck, a motorcar, a wagon-car and a mini-motorcar. The total number memorized in the minicomputer is 432 kinds of motorcar shapes. The number of the matching patterns as a truck is 36. These are similar and generated by neglecting the convex corners. The concave portion is not neglected, because this portion is a specific feature of the shape.
The developed system is featured by the capability of recognizing in less than 3 seconds per one pattern and classifying the patterns into 7 kinds of grouping patterns.
