Abstract The present paper proposes a novel scheme for age group classification based on Third Order Four pixel Pattern (TOFP). This paper identified TOFP patterns in two forms of diamond pattern which have four pixels i.e., outer diamond and inner diamond patterns in Third Order neighborhood. The paper derives Grey-Level Co-occurrence Matrix (GLCM) of a Wavelet image based on the values of Outer Diamond Corner Pixels (ODCP) of TOFP and Inner Diamond Corner Pixels (IDCP) of TOFP on wavelet image which is generated from the original image without using the standard method for generating the co-occurrence matrix. Four GLCM features are extracted from the generated matrix. Based on these feature values, the age group of the human facial image was categorized. In this paper, human age is classified into six age groups such as Child: 0-9 years, Adolescent: 10-19 years, Young Adult: 20-35 years, Middle-Aged Adults: 36-45 years, Senior Adults 46–60 years, Senior Citizen: age > 60. The proposed method is tested on different databases and comparative results are given.

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[29] Yan S., Wang H., Tang X., and Huang T., “Learning Auto-Structured Regressor from Uncertain Nonnegative Labels,” in Proceedings of IEEE 11th International Conference on Computer Vision, Rio de Janeiro, pp. 1-8, 2007. 40 The International Arab Journal of Information Technology, Vol. 16, No. 1, January 2019 Rajendra Chikkala received the B.Tech degree in Computer Science & Engineering from Jawaharlal Nehru Technological University, Hyderabad, India in 2005, M.Tech. degree in Computer Science and Engineering from Acharya Nagarjuna University, India in 2008, and registered for Ph.D. in Computer Science and Engineering at Jawaharlal Nehru Technological University under the guidance of Prof. E. Srinivasa Reddy and Prof. B.Prabhakara Rao. His research interests include Image Processing. Sreenivasa Edara received the B.Tech degree in Electronics and Communication Engineering from Nagarjuna University, India in 1988, M.S. degree from Birla Institute of Technology and Science, India in 1997, M.Tech degree in Computer Science from Visveswaraiah Technological University, India in 2000 and Ph.D in computer science from Acharya Nagarjuna University, India in 2008. He is the senior member of IEEE and presented 11 papers in international conferences and 6 journal papers. Presently working as principal in ANU college of Engineering. His research interest includes image processing, biometrics and pattern recognition. Prabhakara Bhima has more than 28 years of experience in teaching and 20 years of R & D. He is an expert in Signal Processing & Communications. He produced 6 PhD’s and guiding 25 PhD scholars. He held Head of the Department, in JNTU College of Engineering. Presently working as Rector in JNTU Kakinada. He published more than 85 technical papers in national and International journals and conferences.