International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 79 - Issue 13 |
Published: October 2013 |
Authors: V. Vijaya Kumar, Jangala Sasi Kiran, Gorti Satyanarayana Murty |
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V. Vijaya Kumar, Jangala Sasi Kiran, Gorti Satyanarayana Murty . Pattern based Dimensionality Reduction Model for Age Classification. International Journal of Computer Applications. 79, 13 (October 2013), 14-20. DOI=10.5120/13800-1787
@article{ 10.5120/13800-1787, author = { V. Vijaya Kumar,Jangala Sasi Kiran,Gorti Satyanarayana Murty }, title = { Pattern based Dimensionality Reduction Model for Age Classification }, journal = { International Journal of Computer Applications }, year = { 2013 }, volume = { 79 }, number = { 13 }, pages = { 14-20 }, doi = { 10.5120/13800-1787 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2013 %A V. Vijaya Kumar %A Jangala Sasi Kiran %A Gorti Satyanarayana Murty %T Pattern based Dimensionality Reduction Model for Age Classification%T %J International Journal of Computer Applications %V 79 %N 13 %P 14-20 %R 10.5120/13800-1787 %I Foundation of Computer Science (FCS), NY, USA
The two most popular statistical methods used to measure the textural information of images are the Grey Level Co-occurrence Matrix (GLCM) and Texture Units (TU) approaches. The novelty of the present paper is, it combines TU and GLCM features by deriving a new model called "Pattern based Second order Compressed Binary (PSCB) image" to classify human age in to four groups. The proposed PSCB model reduces the given 5 x 5 grey level image into a 2 x 2 binary image, while preserving the significant features of the texture. The proposed method intelligently compressed a 5x5 window into a 2x2 window and derived TU on them. Thus the derived TU also represents a TU of a 5x5 window. The TU of the proposed PSCB model ranges from 0 to 15, thus it overcomes the previous disadvantages in evaluating TU's.