Main Article Content
Biometric face recognition including digital processing and analyzing a subject's facial structure. This system has a certain number of points and measures, including the distances between the main features such as eyes, nose and mouth, angles of features such as the jaw and forehead with the lengths of the different parts of the face. With this information, the implemented algorithm creates a unique model with all the digital data. This model can then be compared with the huge databases of images of the face to identify the subject. The recognition features are retrieved here using histogram equalization technique. A high-resolution result is obtained applying this algorithm under the conditions of a specific image database.
How to Cite
Al-Shayea, Q. K., & Al-Ani, M. (2022). Biometric Face Recognition Based on Enhanced Histogram Approach. International Journal of Communication Networks and Information Security (IJCNIS), 10(1). https://doi.org/10.17762/ijcnis.v10i1.3142 (Original work published April 20, 2018)