Volume 7 Issue 4 - November 2016

  • 1. Age classification with shape patterns derived from central pixel flooding matrix (cpfm) on facial images

    Authors : Chandra Sekhar Reddy P, Bhanu Sreekar Reddy Karumuri

    Pages : 205-211

    DOI : http://dx.doi.org/10.21172/1.74.027

    Keywords : Age classification, CPFM, LTMP, UTMP, and SSP.

    Abstract :

    Humans can easily categorize persons into different age groups from facial images of people. The Age classification based on computer vision has widespread applications. For automatic age classification, in this paper shape patterns on Central Pixel Flooding Matrix (CPFM) are used to classify persons with face images into two classes, child and adult. The CPFM forms a textured image over the facial image by considering neighborhood pixels which have the same intensity as a central pixel. The shape patterns Lower Triangular Matrix Pattern (LTMP), Upper Triangular Matrix Pattern (UTMP) and Tri-Diagonal Matrix Pattern (TDMP) on CPFM of facial images are calculated and these features are used for age classification. The experimental results on the FG-Net aging database have shown that this method is more efficient compared to other methods for age grouping of facial images.

    Citing this Journal Article :

    Chandra Sekhar Reddy P, Bhanu Sreekar Reddy Karumuri, "Age classification with shape patterns derived from central pixel flooding matrix (cpfm) on facial images", Volume 7 Issue 4 - November 2016, 205-211