CAJ | 학술논문

分析传统图像边界跟踪中存在的问题,根据Freeman链码跟踪方法提出一种改进的基于像素顶点矩阵的边界跟踪方法,定义图像的像素顶点矩阵,并利用像素顶点矩阵跟踪边界,制定边界跟踪的搜索规则,同时抽取边界的顶点链码,生成嗣线树结构,用像素顶点的链码值表示边界.实验结果表明,该算法优于一般的链码跟踪方法,具有广泛应用性.
분석전통도상변계근종중존재적문제,근거Freeman련마근종방법제출일충개진적기우상소정점구진적변계근종방법,정의도상적상소정점구진,병이용상소정점구진근종변계,제정변계근종적수색규칙,동시추취변계적정점련마,생성사선수결구,용상소정점적련마치표시변계.실험결과표명,해산법우우일반적련마근종방법,구유엄범응용성.
The problems in traditional image border tracking are analyzed. According to Freeman chain code boundary tracking method, a pixel-based boundary tracking method of vertex is given. The image pixel vertex matrix is defined. The pixel matrix is used to track the boundary vertex. The boundaries track search rules is set up. The apex of the boundary chain code is abstracted, and the tree structure is generated. The pixel vertex chain code value is used to indicate the boundary. Experimental results show this algorithm is better than the Freeman chain code tracking methods, and has a wider versatility.