A Graded Approach for Shape Representation

• Main Authors: Wei Chang. Tsai, 蔡維銓
• Other Authors: Shu Yuen. Hwang
• Format: Others
• Language: en_US
• Published: 1993
• Online Access: http://ndltd.ncl.edu.tw/handle/00199385105635928516

碩士 === 國立交通大學 === 資訊工程研究所 === 81 === Visual concepts involved in real world usually possess graded structures. Generally speaking, macroviews of objects can obtain global perception; conversely, details of objects be obtained by microviews. A really intelligent computer vision system must respond to the visual perception in the similar way as a human does. In graded representation, rough description only needs few important features. The finer the representation would be, the more the features should be included. However, the importance of a feature cannot be easily judged by computer vision systems. Instead of selecting features derived from the primary object, most researcheres employed multiscale or multiresolution approach to reducing the number of selected features. This thesis presents an approach to constructing a graded representation for shapes. A graded shape representation is derived from a set of approximation representations. Each approximation representation is further divided into three levels: pixel level, token level and component level. The contribution of this thesis is that it proposed a new approach to representing object shapes like the perceptive way of human being. The approach also defines a ratio to measure the similarity. Most importantly, an efficient procedure of part decomposition was proposed. As we know, this task is not easy for computer systems.