Using flower pollination algorithm and atomic potential function for shape matching

被引：25

作者：

Zhou, Yongquan ^{[1
,2
]}

Zhang, Sen ^{[1
]}

Luo, Qifang ^{[1
,2
]}

Wen, Chunming ^{[1
]}

机构：

[1] Guangxi Univ Nationalities, Coll Informat Sci & Engn, Nanning 530006, Peoples R China

[2] Guangxi High Sch Key Lab Complex Syst & Computat, Nanning 530006, Peoples R China

来源：

NEURAL COMPUTING & APPLICATIONS | 2018年 / 29卷 / 06期

基金：

美国国家科学基金会;

关键词：

Shape matching; Flower pollination algorithm; Atomic potential matching; Numerical optimization; OPTIMIZATION; RECOGNITION;

D O I：

10.1007/s00521-016-2524-0

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Visual shape matching has been a hot research topic. As a relatively new branch, atomic potential matching (APM) model is inspired by potential field attractions. Compared to the conventional edge potential function (EPF) model, APM has been verified to be less sensitive to intricate backgrounds in the test image and far more cost-effective in the computation process. The optimization process of shape matching can be regarded as a numerical optimization problem, which is disposed by flower pollination algorithm (FPA). This study comprehensively investigates the convergence performances of FPA and the other algorithms in shape matching problem based on APM model. Experimental results of three realistic examples show that FPA is able to provide very competitive results and to outperform the other algorithms.

引用

页码：21 / 40

页数：20

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