Skew Correction for Vehicle License Plates Using Principal Component of Harris Corner Feature

Character segmentation and detection play a very important role in the automatic license plate recognition (ALPR) system. For accurate character segmentation first need is to remove skew from the received license plate. Skew is the angle by which the image seems to be deviated from its perceived steady state position. To solve the problem, a combined approach for skew correction of vehicle license plates (VLP) is proposed which is based on Harris corner detector and principal component analysis (PCA). First, corner points are extracted as features using Harris corner detector. PCA is applied onto these features to find out the principal component in the direction of maximum eigen value. This principal component reflects the skew angle of the plate. Then skew correction of the plate is accomplished. Main advantage of the proposed method is, it is very simple in the skew correction of VLP images and gives accurate results.