Face Recognition: Multi-features Extraction with Parallel Computation for Big Data

The field of face recognition in big data presents both promises and challenges. The promise comprises an innovative application which increases safety, convenience and business prospects. The challenges contain finding the skill to manage the big data, i.e., characteristics like volume, variety, velocity and veracity along with the other challenges of face recognition. The proposed method uses blur and chromatic moment feature extraction with parallel computation in the scene of big data. The predicted result signifies that the proposed method increases the face recognition performance with the reduction in time.