Local Octal Pattern: A Proficient Feature Extraction for Face Recognition

This paper presents a novel and efficient face image representation based on Local Octal Pattern (LOP) texture features. The standard methods viz., the local binary pattern (LBP), the local ternary pattern (LTP) and the local tetra pattern (LTrP) are able to encode with a maximum of four distinct values about the relationship between the referenced pixel and its corresponding neighbors. The proposed method calculates the diagonal, horizontal and vertical directions of the pixels using first-order derivatives. Thereby, it encodes eight distinct values about the relationship between the referenced pixel and its neighbors. The performance of the proposed method is compared with the LBP, the LTP and the LTrP based on the results obtained in terms of average precision and average recall on PubFig image database.