Affine invariant matching of broken boundaries based on simple genetic algorithm and contour reconstruction

被引:8
作者
Tsang, P. W. M. [1 ]
Situ, W. C. [1 ]
机构
[1] City Univ Hong Kong, Dept Elect Engn, Hong Kong, Hong Kong, Peoples R China
关键词
Affine invariant matching; Fragmented contours; Contour reconstruction; Simple genetic algorithm; Migrant principle; Quality migrants; RECOGNITION; SHAPES;
D O I
10.1016/j.patrec.2010.01.024
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Viewpoint independent identification of fragmented object contours can be accomplished by matching them against a collection of known reference models. For the class of near-planar objects, the matching process can be posed as the search for the existence of an affine transform between a pair of contours. Recently, it has been demonstrated that the search process can be accomplished with the integration of a simple genetic algorithm (SGA) and a quality migrant injection (QMI) operation. The performance is superior to prior arts based on the use of SGA alone in terms of success rates and computation speed. The downside of such approach is the need of more computation time for generating quality migrants in the course of evolution. In this paper, we have proposed a solution to overcome this problem. Our method has two major contributions. The first one is a scheme which enables a closed boundary to be extracted from a set of fragmented object points, and represented as a one-dimensional (1 - D) sequence. Second, we have applied SGA to determine the similarity between a pair of closed boundaries by searching the existence of three correspondence point pairs in their I - D sequences. As a result of these two contributions, the proposed method is substantially faster than the SGA-QMI scheme, and also capable of attaining close to 100% success rate in identifying matched contours. (c) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码:771 / 780
页数:10
相关论文
共 27 条
[1]  
Adamek Tomasz., 2003, P 5 ACM SIGMM INT WO, P138
[2]   HIERARCHICAL CHAMFER MATCHING - A PARAMETRIC EDGE MATCHING ALGORITHM [J].
BORGEFORS, G .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1988, 10 (06) :849-865
[3]  
CHAKER F, 2007, IAPR C MACH VIS APPL, P291
[4]  
Golberg D. E., 1989, GENETIC ALGORITHMS S, V1989, P36
[5]  
Holland J.H., 1992, Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence
[6]   Evaluation of genetic operators and solution representations for shape recognition by genetic algorithms [J].
Khoo, KG ;
Suganthan, PN .
PATTERN RECOGNITION LETTERS, 2002, 23 (13) :1589-1597
[7]   Discrete contours in multiple views: approximation and recognition [J].
Kumar, MP ;
Goyal, S ;
Kuthirummal, S ;
Jawahar, CV ;
Narayanan, PJ .
IMAGE AND VISION COMPUTING, 2004, 22 (14) :1229-1239
[8]   An optimization approach to shape matching and recognition [J].
Lim, HS ;
Cheraghi, SH .
COMPUTERS & ELECTRICAL ENGINEERING, 1998, 24 (3-4) :183-200
[9]   Partial shape matching using genetic algorithms [J].
Ozcan, E ;
Mohan, CK .
PATTERN RECOGNITION LETTERS, 1997, 18 (10) :987-992
[10]  
RUBE IAE, 2004, P 17 ICPR 04