Title :
Insect classification using Scanning Electron Microphotographs considering magnifications
Author :
Takahashi, Asami ; Ogawa, Tomomi ; Haseyama, Miki
Author_Institution :
Grad. Sch. of Inf. Sci. & Technol., Hokkaido Univ., Sapporo, Japan
Abstract :
This paper presents a method of insect classification using images taken by Scanning Electron Microscope (SEM) considering magnifications. Generally, when images of the same insects are taken by SEM with different magnifications, visual features of these images are different from each other. Thus, the proposed method adopts a new scheme which groups images of different magnifications in such a way that the classification performance becomes the highest. Then a classifier is constructed for each group, and the insect classification becomes feasible based on a target image magnification. In addition, by integrating the classification results of several images obtained from the same sample, i.e., the same insect, performance improvement of the insect classification considering magnifications can be realized. Experimental results show the effectiveness of the proposed method.
Keywords :
biology computing; feature extraction; image classification; scanning electron microscopes; SEM; classification performance; image grouping; insect classification; magnifications; scanning electron microphotographs; scanning electron microscope; target image magnification; visual features; Insect classification; grouping scheme; scanning electron microscope; support vector machine;
Conference_Titel :
Image Processing (ICIP), 2013 20th IEEE International Conference on
Conference_Location :
Melbourne, VIC
DOI :
10.1109/ICIP.2013.6738673