Hand-drawing figure recogniton and similarity measurement

• Main Authors: Liao, H.W., 廖鴻文
• Other Authors: Kuo-Chin Fan
• Format: Others
• Language: zh-TW
• Published: 1997
• Online Access: http://ndltd.ncl.edu.tw/handle/58021114635172083881

碩士 === 國立中央大學 === 資訊工程研究所 === 85 === ABSTRACT In this thesis, we try to solve two hand-drawing relating problems They are hand-drawing symbol recognition and hand-drawing figure similarity measurement. The solutions to these two problems let computer be more complaisant and more convenient to the users. In the first task, the objects to be recognized here are symbols which are composed of fundamental figures, such as "upward arrow", "delete" etc. A new scheme for hand-drawing symbol recognition using fundamental figure extraction algorithm has been suggested. The proposed scheme imposes no restriction on stroke sequence and scale. In the second task, the goal is to decide the similarity between two hand-drawing figures. A data structure called hierarchical interrelated tree (HIT) is proposed to represent a hand-drawing object. The hierarchical interrelation tree is effective to decompose the figure and reduce the evaluation time of similarity measurement. Besides, a novel method is proposed to measure the similarity between two HITs. It is consistent with the human visual interpretation and gives a better way for evaluating the similarity between two hand-drawing figures. In addition, we develop a content-based image retrieval system that uses the HIT of a sketched image to retrieve similar images from the image database. An index structure, basic shape description, is proposed to implement the candidate selection. It is efficient to quicken the retrieval time and have high accuracy on selecting candidates. Experimental results show that the application using these methods is feasible and has high accuracy on retrieving images.