A KNOWLEDGE-BASED THINNING ALGORITHM

被引:19
作者
LI, B
SUEN, CY
机构
[1] Centre for Pattern Recognition and Machine Intelligence, Concordia University, Montreal, Que. H3G 1M8
基金
加拿大自然科学与工程研究理事会;
关键词
THINNING; SKELETONIZATION; KNOWLEDGE-BASED THINNING; PREPROCESSING;
D O I
10.1016/0031-3203(91)90146-V
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
One common defect of thinning algorithms is deformation at crossing points. To solve this problem, a new thinning method, called the knowledge-based thinning algorithm (KBTA), is proposed, It first represents a binary pattern by coded run lengths of the horizontal line segments. Then the relationship between line segments is described quantitatively by another new algorithm which makes use of both forward and backward derivatives, It afterwards identifies the regions where branches of the pattern meet, then extracts their shape features and thins all of them. Knowing the identities of these regions, perfect skeletons can be obtained. Other regions are thinned by an existing algorithm which is based on contour generation. Experiments with a wide variety of binary patterns show that this new technique generates better skeletons than several other well-known algorithms.
引用
收藏
页码:1211 / 1221
页数:11
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