计算机科学与探索Issue(10)：1263-1270,8.DOI:10.3778/j.issn.1673-9418.1502015
基于改进弹性网格的古民居指纹分类算法
Ancient house fingerprint classification algorithm based on improved elastic grid
摘要
Abstract
House goals are separated from satellite image by using rectangle algorithm based on area feature and shape feature, and the mistakenly identified objects need to be eliminated from all separated objects based on their different texture features. Rotating, enlarging and cutting operations need to be designed to make those separated objects standardize with same size and direction. Elastic grid technique can choose several characteristic lines and columns of the image, and the intersections of them can partition an image into several characteristic grids. The classic relevant statistics of gray level co-occurrence matrix (GLCM) of each grid are computed to generate a characteristic fingerprint array, which comprehensively reflect the local texture features of the grid. The combination of finger-print arrays of all grids can generate the fingerprint vector of an image, which can reflect global features of the image. The feature vector generated from improved elastic grid partition and GLCM statistic can simultaneously characterize the local texture features and global statistic features of an image. Ancient houses are accurately identified and clas-sified by the similarity comparison to house samples of different periods based on their characteristic fingerprint vec-tors. Experiments show that the correct rate of separated house targets is about 86.9%by using rectangle algorithm, and using the house fingerprint algorithm based on elastic grid partition and GLCM statistics, the correct prelimi-nary classification rate of ancient houses is more than 97.4%.关键词
矩形算法/灰度共生矩阵(GLCM)/弹性网格/指纹/民居分类Key words
rectangle algorithm/gray level co-occurrence matrix (GLCM)/elastic grid/fingerprint/house classification分类
信息技术与安全科学引用本文复制引用
杨帆,沈来信..基于改进弹性网格的古民居指纹分类算法[J].计算机科学与探索,2015,(10):1263-1270,8.基金项目
The Science Innovation Project of Ministry of Culture of China under Grant No. WHBKJCXXM20142554(文化部科技创新项目) （文化部科技创新项目）
the Cultural Preservation and Technological Research Program of State Administration of Cultural Heritage of China under Grant No.2013-YB-SQ-175(文物局文化保护和技术研究课题) （文物局文化保护和技术研究课题）
the Scientific Research Project of Huangshan University under Grant No.2015xhwh012(黄山学院校级科研项目) （黄山学院校级科研项目）
