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A Support Vector Machine (SVM) implemented with OpenCV used for classification of benign and malignant Melanoma images.

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About

This code shows the OpenCV's implementation of Support Vector Machines (SVM). I implemented and trained it to classify benign and malignant Melanoma images. There's a post on my blog about it.

If you'd like, it's possible to train it using another kind of pictures.

Compiling

You will need OpenCV with contrib modules. Considering the OpenCV folders C:\\opencv-master\\mingw_build\\install\\include and C:\\opencv-master\\mingw_build\\install\\x86\\mingw\\lib:

G++

  1. cd src

  2. g++ "-IC:\\opencv-master\\mingw_build\\install\\include" -O0 -g3 -Wall -c -fmessage-length=0 -std=c++14 -o "OPENCVSVM.o" "OPENCVSVM.cpp"

  3. g++ "-LC:\\opencv-master\\mingw_build\\install\\x86\\mingw\\lib" -o OPENCVSVM.exe "OPENCVSVM.o" -lopencv_calib3d330 -lopencv_imgcodecs330 -lopencv_imgproc330 -lopencv_ml330 -lopencv_objdetect330 -lopencv_photo330 -lopencv_shape330 -lopencv_core330 -lopencv_features2d330 -lopencv_highgui330

Results

I selected 26 random images from International Society for Digital Imaging of the Skin (ISDIS) database, 13 from benign and 13 malignant lesions. From that, 20 were used in the training process and 6 (3 malignant and 3 benign) in the validation. The SVM achieved the expected values in 100% of the cases.

About

A Support Vector Machine (SVM) implemented with OpenCV used for classification of benign and malignant Melanoma images.

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