基于分块不变矩特征的瓷砖分类识别的研究  

Ceramic tile classification and recognition based on sub-block invariant moment

作　　者：卞玉丽[1] 郑力新[1] 晏来成[1] 徐园园[1] 

机构地区：[1]华侨大学信息科学与工程学院,福建厦门361021

出　　处：《微型机与应用》2011年第24期32-35,共4页Microcomputer & Its Applications

基　　金：福建省产业计划开发项目(25201071);泉州市科技计划项目(2010G1);福建省高等学校新世纪优秀人才支持计划(07FJRC01)

摘　　要：首先通过形态学边缘检测方法提取瓷砖花纹,然后采用分块提取特征的思想对瓷砖进行分类识别,即先将瓷砖分成4行4列16个子块,然后提取每子块两个稳定的Hu不变矩,共32个不变矩作为瓷砖分类的特征向量。对于分块后造成的矩的位置相关性问题,通过将每个训练样本分别旋转90°、180°、270°,然后再提取它们的矩特征向量的方法来解决。最后将提取到的特征向量输入BP神经网络进行分类识别。测试结果表明,本方法识别准确率高、运算速度快,能达到预期目的。This paper involves morphological edge detection method by extracting tile pattern, and then use the block feature extraction for classification and recognition ideas on tile. Ceramic tile is firstly divided into 16 sub-blocks of 4 lines 4 and then extracted two invariant moments for each sub-block. So a total of 32 moments constitute the feature vector for tile classification. With the Hu moment is sensitive to location, because the division of the tile into sub-blocks, so it rotates each training sample 90,180 and 270 degrees in order to eliminate the in order to eliminate the negative influence. Finally, do the test with the extract feature vectors as the input of BP neural network. The results show that this method of identification is fast with high accuracy and achieve the desired purpose.

关 键 词：边缘检测 不变矩 神经网络 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]