Applying the significance degree by SOM to image analysis of fundus using the filter bank

This paper describes the filtering effects on classification performance with applying significance degree by SOM to the image analysis using filter bank preprocessing and Subspace Classifier. In our proposed method, a series of analysis concerning accuracy were first conducted in the cases of single filter and filter bank, and examinations on significance degree by SOM were conducted based on green(G) and blue(B) color channels. The difference of the filtering effect between two color channels was compared with using the significance degree. We show that the difference of the filtering effect between two channels can be clarified by using the significance degree by SOM.

[1]  Jorma Laaksonen,et al.  Comparison with Observer Appraisals of Fundus Images and Diagnosis by using Learning Vector Quantization , 2007 .

[2]  Jorma Laaksonen,et al.  Fundus Image Analysis Using Subspace Classifier and its Performance , 2010 .

[3]  Nobuo Matsuda,et al.  Low-pass Filter's Effects on Image Analysis Using Subspace Classifier , 2014, Advanced Intelligent Systems.

[4]  Makoto Ohki,et al.  The new proposal of the calculation for the significance degree by once SOM learning — Using iris, gene, and Tof-SIMS data , 2014, 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems (SCIS) and 15th International Symposium on Advanced Intelligent Systems (ISIS).

[5]  Nobuo Matsuda,et al.  Image Analysis of Fundus Using Filter Bank and Subspace Classifier , 2016, 2016 International Conference on Computational Science and Computational Intelligence (CSCI).

[6]  MalikJitendra,et al.  Representing and Recognizing the Visual Appearance of Materials using Three-dimensional Textons , 2001 .

[7]  Shigeaki Watanabe,et al.  Subspace method to pattern recognition , 1973 .

[8]  Nobuo Matsuda,et al.  Filtering Effects for Image Data Types in Image Analysis Using Subspace Classifier , 2016, 2016 Joint 8th International Conference on Soft Computing and Intelligent Systems (SCIS) and 17th International Symposium on Advanced Intelligent Systems (ISIS).

[9]  Jitendra Malik,et al.  Representing and Recognizing the Visual Appearance of Materials using Three-dimensional Textons , 2001, International Journal of Computer Vision.