一种人工免疫算法优化SVC的桥体图像裂痕识别方法  

A Kind of Artificial Immune Algorithm to Optimize the SVC Computer Identification of Crack Identification Method

作　　者：底素卫[1] 

机构地区：[1]河北建筑工程学院,河北张家口075000

出　　处：《科技通报》2013年第8期88-90,共3页Bulletin of Science and Technology

基　　金：河北省教育厅自然科学研究治疗项目(2008435)

摘　　要：针对当桥梁体建筑开裂程度细微或者裂痕的特征发生混淆时,以此建立的高斯模型会发展特征混合,很难准确区分待识别特征,为了解决这一问题,提出一种人工免疫算法优化SVC的计算机裂痕识别方法,通过对裂痕特征进行预处理,建立支持向量机的模型对混叠的细微特征进行分类,运用人工免疫算法对分类的效果进行优化处理,解决由于灰度特征发生错误,桥梁桥体裂痕识别准确度不高的问题。实验证明,这种裂痕识别算法实现简单,能够克服裂痕特征过于细微带来的缺陷,得到了较好的识别效果。For when the bridge wall building cracking degree fine or crack characteristics occur when confusion, this pa- per builds up the gaussian model will be mixed development characteristics, it is difficult to accurately distinguish to i- dentification characteristics, in order to solve this problem, the paper proposes a kind of artificial immune algorithm to optimize the SVC computer identification of crack identification method, through the crack characteristics of pretreatment, through the establishment of support vector machine （SVM） model of aliasing subtle features of classification, the use of the artificial immune algorithm [br classification effect optimized, solve the grayscale characteristics mistakes, Bridges wall crack identification accuracy is not high question. Experiments show that the crack identification algorithm is simple, can overcome crack characteristics is too small to bring defects and obtain the better identification effect

关 键 词：裂痕识别 人工免疫 支持向量机 

分 类 号：TN973.3[电子电信—信号与信息处理]