A New Hough Transform on Face Detection and Recognition Using Integrated Histograms

A B S T R A C T Hough Transform (HT) is one of the useful algorithms in pattern recognition. It is popularly used to detect straight lines, circles and curves in images. This study discovered a new feature detection and extraction using the HT. The intensity of the input image was enhanced and histogram plot of the stretched image was obtained. However, HT functions perform transformation of Hough matrix, locate peak values and superimpose a plot on the features representing the original image. Hence, face features were detected and the extracted features proceeded for verification. Cross Correlation Technique (CCT) and Euclidean Distance (ED) were computed to determine the similarity between test images and neutral image. The experiment on FEI face database demonstrated the effectiveness of the new technique and obtained recognition with minimal error. Furthermore, the application of HT was improved and the benefits of the proposed algorithm were verified. It is believed that, the discovery is new in the domain.