Age Classification Based On Integrated Approach

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Author(s)

Pullela. SVVSR Kumar 1,* V.Vijayakumar 2 Rampay.Venkatarao 3

1. V.S. Lakshmi Engineering College for Women, Kakinada, India

2. Anurag Group of Institutions, Hyderabad, India

3. GITAM Institute of Technology, Vishakhapatnam, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijigsp.2014.06.07

Received: 10 Jan. 2014 / Revised: 21 Feb. 2014 / Accepted: 9 Apr. 2014 / Published: 8 May 2014

Index Terms

Age classification, Combined feature, Distinct-LBP, Fuzzy Texture, GLCM, Patterns

Abstract

The present paper presents a new age classification method by integrating the features derived from Grey Level Co-occurrence Matrix (GLCM) with a new structural approach derived from four distinct LBP's (4-DLBP) on a 3 x 3 image. The present paper derived four distinct patterns called Left Diagonal (LD), Right diagonal (RD), vertical centre (VC) and horizontal centre (HC) LBP's. For all the LBP's the central pixel value of the 3 x 3 neighbourhood is significant. That is the reason in the present research LBP values are evaluated by comparing all 9 pixels of the 3 x 3 neighbourhood with the average value of the neighbourhood. The four distinct LBP's are grouped into two distinct LBP's. Based on these two distinct LBP's GLCM is computed and features are evaluated to classify the human age into four age groups i.e: Child (0-15), Young adult (16-30), Middle aged adult (31-50) and senior adult (>50). The co-occurrence features extracted from the 4-DLBP provides complete texture information about an image which is useful for classification. The proposed 4-DLBP reduces the size of the LBP from 6561 to 79 in the case of original texture spectrum and 2020 to 79 in the case of Fuzzy Texture approach.

Cite This Paper

Pullela. SVVSR Kumar, V.Vijaya Kumar, Rampay.Venkatarao,"Age Classification Based On Integrated Approach", IJIGSP, vol.6, no.6, pp.50-57, 2014. DOI: 10.5815/ijigsp.2014.06.07

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