Face Sketch Recognition: Gender Classification and Recognition - Ounachad, Khalid; Oualla, Mohamed; Sadiq, Abdelalim; Sohar, Abdelghani (International Journal of Psychosocial Rehabilitation, 2020)
The main objective of this paper is to identify the gender of the human being based on their face sketch by using a geometric feature. This paper presents a novel method for human face sketch gender classification and recognition. We generate two referential faces suitable for each kind of facial gender based on perfect face ratios and five classical averages. The basic idea is to extract perfect face ratios for the input face sketch and for each referential face as features and calculate the distance between them by using fuzzy Hamming distance. To extract perfect face ratios, we use the point landmarks in the face then sixteen features will be extract. An experimental evaluation demonstrates the satisfactory performance of our approach on the CUHK Face Sketch dataset (CUFS). It can be applied with any existing face sketch dataset. The proposed algorithm will be a competitor of the other proposed relative approaches. The recognition rate reaches more than 88% (60% for females and more than 86% for males).