沈阳工业大学学报2017，Vol.39Issue(3)：292-298,7.DOI:10.7688/j.issn.1000-1646.2017.03.10
基于蜂群单阈值分割的SRC板材缺陷分类方法
Classification method for SRC wooden board defects based on single threshold segmentation of artificial bee colony
摘要
Abstract
Aiming at such shortages as easily falling into local optimum situation, precocity and slow convergence speed of traditional single threshold segmentation algorithm for wooden board defects, a single threshold segmentation algorithm based on improved artificial bee colony (ABC) algorithm was proposed.In order to improve the defect classification accuracy and reduce the computational work, the sparse representation-based classifier (SRC) was applied in the classification process of wooden board defects.The improved algorithm simultaneously could realize both global and local search during each iteration, and the bee scouts could select nectar resources randomly in global area to speed up the convergence rate.The search radius was adaptively adjusted according to time-varied search parameters, and the SRC transformed the defect classification problem into the problem of obtaining the most sparse coefficient solution.The results show that the proposed algorithm can compute the optimal segmentation threshold, improve the classification accuracy to above 90%, and has certain reliability and feasibility.关键词
板材缺陷/蜂群算法/单阈值分割/蜜源/稀疏表达分类器/搜索半径/时变搜索参数/最稀疏系数Key words
wooden board defect/artificial bee colony algorithm/single threshold segmentation/nectar resource/sparse representation-based classifier/search radius/time-varied searching parameter/most sparse coefficient分类
信息技术与安全科学引用本文复制引用
魏晓慧,马晓珍,刘亚秋..基于蜂群单阈值分割的SRC板材缺陷分类方法[J].沈阳工业大学学报,2017,39(3):292-298,7.基金项目
国家自然科学基金资助项目(31370565) （31370565）
哈尔滨市科技创新人才研究专项基金资助项目(2015RAYXJ005). （2015RAYXJ005）
