資源簡介
PCA/SVM算法實現圖像分類,分類準確率可到達90%
代碼片段和文件信息
%{
***************************************************************************
????
????Cheng?Gong
????2017-6-24
????智能信息處理作業
????本次作業目的是對徑向干擾圖片、螺旋狀干擾圖片、麻點狀干擾圖片三類圖片進行分類,
????最終利用的方法是PCA+SVM,即主成分分析法和支持向量機結合的方法。
????訓練圖片是15張,測試圖片5張
***************************************************************************
%}
%main?函數是主函數
clear?
close?all
tic
%%
%?批量讀取指定文件夾下的圖片
disp(‘訓練圖片集路徑:E:\MatlabProgram\作業工程\智能信息處理3.0\train‘);
pathname?=?‘E:\MatlabProgram\作業工程\智能信息處理3.0\train‘;
disp(‘正在讀取圖片...‘);
img_path_list?=?dir(strcat(pathname‘\*.png‘));
img_num?=?length(img_path_list);
imagedata?=?[];
if?img_num?>0
????for?j?=?1:img_num
????????img_name?=?img_path_list(j).name;
????????temp?=?imread(strcat(pathname?‘/‘?img_name));
????????temp?=?imresize(temp[370370]);
????????temp?=?double(temp(:));
?
?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????目錄???????????0??2017-07-01?11:58??PCA-SVM-master\
?????文件???????????5??2017-07-01?11:58??PCA-SVM-master\.gitignore
?????文件?????????123??2017-07-01?11:58??PCA-SVM-master\README.md
?????文件????????2730??2017-07-01?11:58??PCA-SVM-master\main.m
?????文件?????????525??2017-07-01?11:58??PCA-SVM-master\multiSVM.m
?????文件?????????606??2017-07-01?11:58??PCA-SVM-master\multiSVMtrain.m
?????文件????????1917??2017-07-01?11:58??PCA-SVM-master\test.m
?????目錄???????????0??2017-07-01?11:58??PCA-SVM-master\test\
?????文件???????44077??2017-07-01?11:58??PCA-SVM-master\test\0?(1).png
?????文件???????72411??2017-07-01?11:58??PCA-SVM-master\test\0?(2).png
?????文件???????38049??2017-07-01?11:58??PCA-SVM-master\test\0?(3).png
?????文件???????35242??2017-07-01?11:58??PCA-SVM-master\test\0?(4).png
?????文件???????30781??2017-07-01?11:58??PCA-SVM-master\test\0?(5).png
?????文件??????156468??2017-07-01?11:58??PCA-SVM-master\test\1?(1).png
?????文件???????62669??2017-07-01?11:58??PCA-SVM-master\test\1?(2).png
?????文件??????107671??2017-07-01?11:58??PCA-SVM-master\test\1?(3).png
?????文件???????80643??2017-07-01?11:58??PCA-SVM-master\test\1?(4).png
?????文件???????55553??2017-07-01?11:58??PCA-SVM-master\test\1?(5).png
?????文件???????55868??2017-07-01?11:58??PCA-SVM-master\test\2?(1).png
?????文件???????38445??2017-07-01?11:58??PCA-SVM-master\test\2?(2).png
?????文件???????29013??2017-07-01?11:58??PCA-SVM-master\test\2?(3).png
?????文件???????23713??2017-07-01?11:58??PCA-SVM-master\test\2?(4).png
?????文件???????22353??2017-07-01?11:58??PCA-SVM-master\test\2?(5).png
?????目錄???????????0??2017-07-01?11:58??PCA-SVM-master\train\
?????文件???????44077??2017-07-01?11:58??PCA-SVM-master\train\0?(1).png
?????文件???????27757??2017-07-01?11:58??PCA-SVM-master\train\0?(10).png
?????文件???????56032??2017-07-01?11:58??PCA-SVM-master\train\0?(11).png
?????文件???????96927??2017-07-01?11:58??PCA-SVM-master\train\0?(12).png
?????文件???????77765??2017-07-01?11:58??PCA-SVM-master\train\0?(13).png
?????文件???????42728??2017-07-01?11:58??PCA-SVM-master\train\0?(14).png
?????文件???????67671??2017-07-01?11:58??PCA-SVM-master\train\0?(15).png
............此處省略40個文件信息
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