Aspect Vision Based on Outline Images
Masao Izumi, Hiroki Kawakami, Takashi NISHIMURA, Kunio Fukunaga · Transactions of the Institute of Systems Control and Information Engineers · 1992
We propose a method of object recognition using the knowledge of the object world described in a form of a frame structure. The hierarchical frame structure consists of two levels, an outline image level and an aspect graph level. Using this database, we can recognize input as an object that has the largest degree of similarity between input edge image and outline images and/or aspect graphs in the database. Firstly, we calculate-the degree of similarity between the input image and images in the database on the outline level in order to narrow down the candidates. Next, we calculate the degree of similarity between the input image and the candidates in the database on the aspect level. In this point, it is available to recognize objects on high recognition rates and high speed. In the case that the object world consists of five kinds of chairs composed by polygonal surfaces, we show some experimental results.