Automatic image analysis methods for use with local operators

Just as image processing and image data bases have moved out of the lab and into the office environment, so has the need for image enhancement. Image scanners must to be able to capture and store a wide variety of information including faded documents, carbon copies, signatures, postmarks, etc. OCR systems put further demands on scanned image quality in terms of low noise, and unbroken disconnected characters. Straight thresholding techniques do not always meet the performance requirements, but by applying simple image processing techniques some of these problems can be solved. However, more burden is placed on the users to control the image enhancement techniques. The users, most of whom have little technical background, want no part in adjusting parameters. This paper proposes a method of examining small windows of the image to derive parameter settings autonomously. Histograms allow rudimentary measures to be used in setting parameters for edge detection, non-linear filters, and point operators such as non-linear gray scale mapping. Some examples of automatic parameter setting are given in chapter three.