Performance analysis on image acquisition techniques in edge detection

Abstract

Image Acquisition is the first stage of any vision systems that refers to the collection of data required to form an image. This paper consider three image acquisition methods such as Traditional Monocular vision, RTI (Reflectance Transformation Imaging) and Proposed shadow Stereopsis. These acquired images are then applied into edge detection process for comparison. Analysis are performed in terms of computation time and various performance measures such as Hamming distance, Peak Signal to Noise Ratio(PSNR) and Mean Square Error(MSE). Comparisons with the best available results are given in order to illustrate the best possible technique that can be used as powerful image acquisition method. This paper helps us for improving the perception of details, features and overall shape characteristics from images which are further useful in the study of ancient archeological stone writings.