Brain CT-Scan Images Classification Using PCA, Wavelet Transform and K-NN

Kamaljeet Kaur, Daljit Singh


With rapid development of technology in biomedical image processing, classification of tissues of human body is very challenging task as it requires very accurate results without any misclassification. By making use of this technology along with neural network; a hybrid technique has been proposed for classification of Brain CT-Scan images. This technique is not limited to medical field; it is also applicable to classification of natural images. Database consists of CT-Scan images and Brodatz texture. The methodology adopted in this paper consists of two stages: firstly, features are extracted from given images using feature extraction algorithms PCA and Wavelet Transform. They are further fed as an input to train the K-NN classifier to classify between normal and abnormal images. For Brain CT-Scan images; features extracted by PCA gives 100% classification accuracy with execution time of 0.6133 seconds whereas for Brodatz texture images; features by Wavelet transform gives classification accuracy of 100% with execution time of 0.1912 seconds. Code is developed by using MATLAB 2011a.


CT-Scan, PCA, GLCM, K-NN, feature extraction


Amir Rajaei, Lalitha Rangarajan, “Wavelet Based Feature Extraction for Medical Image Classification”. An International Journal of Engineering Sciences, ISSN: 2229-6913 Issue Sept 2011, Vol.4.

EL-Sayed, EL- Dahshan, Abdul- Badeeh M. Salem, Tamer H.Yousin, “A Hybrid Technique for Automatic MRI Brain Images Classification”. Studia Univ. Babes.Bolyai, Volume LIV, Number 1, 2009.

M.Vasantha, “Medical Image Feature Extraction, Selection and Classification”, International Journal of Engineering Science and Technology, Vol.2 (6), 2010, 2071-2076.

Manimegalai.P, Revathy.P, Dr.K.Thanushkodi, “Micro-calcification Detection in Mammogram Image using Wavelet Transform and Neural Network” .International Journal of Advanced Scientific Research and Technology. Issue2.Volume 1(February 2012). ISSN: 2249-9954.

R.Nithya, B.Santhi, “Comparative Study on Feature Extraction Method for Breast Cancer Classification” Journal of Theoretical and Applied Information Technology, 30 Nov, 2011. Vol.33 No.2, ISSN: 1992 - 86

Ms.Yogita K.Dubey, Milind M. Mushrif, “Extraction of Wavelet Based Features for Classification of T2-Weighted MRI Brain Images”. Signal and Image Processing: International Journal (SIPIJ) Vol.3, No.1, February 2012.

N.Suguna, Dr. K.Thanushkodi, “An improved K-nearest neighbor classification using Genetic Algorithm” IJCSI- International Journal of Computer Science Issues, Vol.7 , Issue-4, July 2010. ISSN: 1694-0784

Ryszard S.Choras, “Image Feature Extraction Techniques and Their Applications for CBIR and Biometrics Systems”, International Journal of Biology and Biomedical Engineering. Issue 1, Vol.1, 2007.

Full Text: PDF


  • There are currently no refbacks.


Index by:

All Rights Reserved © 2012 IJARCSEE

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 Unported License.