Ensembled IALTP Feature Descriptors and Support Vector Machine Classification for Face Recognition

T. Shanthi,P.Radha

In the fields of computer vision and important tasks the most vital mission besides the machine learning and artificial intelligence is the Face Recognition. The large variants of the prevailing approaches on face recognition concentrates on the recognition of the utmost appropriate facial attributes for efficiently recognizing and differentiating amongst the considered images. This methodology uses an improvised technique of ALTP descriptors along with the classification of face recognition in the biometrics. In wild environment by the of ensemble of descriptor characteristics and the preprocessing approaches is used in this paper to establish an ensemble assisted recognition of face approach which is recommended for a good performance. Support vector machine algorithm had been used for classifying and preprocessing the facial images which are excavated by the blend of texture and color descriptors. The experimental outcome of the suggested methodology is illustrated using the database such as FERET data samples in the Wild data samples. So, the results states that the examples of the data samples provide the outcomes as the proposed data methodology has a great organization accuracy and blend usage of the preprocessing systems because of the further extracted feature descriptor and preprocessing. The moderate classification precisions for the data samples is 99%.

Volume 12 | Issue 6

Pages: 1981-1988

DOI: 10.5373/JARDCS/V12I2/S20201403