文献类型：会议论文

英文题名：Feature Extraction of Human Viruses Microscopic Images Using Gray Level Co-occurrence Matrix

作者：Liu, Qing[1];Liu, Xiping[2]

第一作者：Liu, Qing

通信作者：Liu, Q[1]

机构：[1]Tianshui Normal Univ, Sch Phys & Informat Sci, Tianshui, Peoples R China;[2]Gansu Univ TCM, Dept Basic Med Sci, Lanzhou, Peoples R China

第一机构：Tianshui Normal Univ, Sch Phys & Informat Sci, Tianshui, Peoples R China

通信机构：[1]corresponding author), Tianshui Normal Univ, Sch Phys & Informat Sci, Tianshui, Peoples R China.

会议论文集：International Conference on Computer Sciences and Applications (CSA)

会议日期：DEC 14-15, 2013

会议地点：Hubei Univ Technol, Wuhan, PEOPLES R CHINA

主办单位：Hubei Univ Technol

语种：英文

外文关键词：feature extraction; GLCM; human viruses microscopic images

年份：2013

摘要：With the development of information technology in biomedical signal detection, processing and digital image signal processing, the role of automatic visual recognition becomes more important. In this paper, in order to effectively extract the feature information of human viruses (HV) microscopic images, an algorithm of HV microscopic image feature extraction and recognition using gray level co-occurrence matrix (GLCM) is proposed. Firstly, 20 pieces of microscopic images of human virus are obtained by using GLCM, and then the four texture feature parameters, entropy, energy, inertia moment and correlation are extracted utilizing the GLCM, and then HV image recognition is carried out. The experimental results show that the GLCM and extraction of image texture features can effectively identify the HV image, which can bring significance to the modern recognition and identification of HV