A Transform Domain Modular approach for facial recognition using different representations and windowing techniques

A face recognition algorithm based on a newly developed Transform Domain Modular (TDM) approach is proposed. In this approach, the spatial faces are divided into smaller sub-images, which are processed using non-overlapping and overlapping windows. Each image is subsequently transformed using a compressing transform such as the two dimensional discrete cosine transform. This produces the TDM-2D and the TDM-Dia based on two-dimensional and diagonal representations of the data, respectively. The performance of this approach for facial image recognition is compared with the state of the art successful techniques. The test results, for noise free and noisy images, yield higher than 97.5% recognition accuracy. The improved recognition accuracy is achieved while retaining comparable or better computation complexity and storage savings.