Insect recognition based on integrated region matching and dual tree complex wavelet transform

作     者：Le-qing ZHU Zhen ZHANG 

作者机构：College of Computer Science and Information Engineering Zhejiang Gongshang University Hangzhou 310018 China Key Lab of Forest Protection of State Forestry Administration Research Institute of Forest Ecology Environment and Protection Chinese Academy of Forestry Beijing 100091 China 

出 版 物：《Journal of Zhejiang University-Science C(Computers and Electronics)》 (浙江大学学报C辑（计算机与电子（英文版）)

年 卷 期：2011年第12卷第1期

页      面：44-53页

核心收录：

学科分类：08[工学] 080203[工学-机械设计及理论] 0802[工学-机械工程] 

基　　金：Project (No.2006AA10Z211) supported by the National High-Tech Research and Development Program (863) of China 

主　　题：Lepidopteran insects Auto-classification k-means algorithm Integrated region matching (IRM) Dual tree complex wavelet transform (DTCWT) 

摘      要：To provide pest technicians with a convenient way to recognize insects,a novel method is proposed to classify insect images by integrated region matching (IRM) and dual tree complex wavelet transform (DTCWT).The wing image of the lepidopteran insect is preprocessed to obtain the region of interest (ROI) whose position is then *** ROI is first segmented with the k-means algorithm into regions according to the color features,properties of all the segmented regions being used as a coarse level *** color image is then converted to a grayscale image,where DTCWT features are extracted as a fine level *** IRM scheme is undertaken to find K nearest neighbors (KNNs),out of which the nearest neighbor is searched by computing the Canberra distance of DTCWT *** method was tested with a database including 100 lepidopteran insect species from 18 families and the recognition accuracy was 84.47%.For the forewing subset,a recognition accuracy of 92.38% was *** results showed that the proposed method can effectively solve the problem of automatic species identification of lepidopteran specimens.