Subpixel Edge Reconstruction using Aliased Pixel Brightness

Abstract

One of the most common image features used in machine vision are edges, and there is a substantial body of research on various techniques for performing edge detection. Edges are useful in many applications as image comparing, recognition and other. Here is presented edge detection method with subpixel accuracy. Method is based on decision that different intensity and size areas influence pixel brightness with some relation function. Hear presented functions to calculate one dot of edge going through the pixel. Test results show that with 0.01 standard deviation is estimated 47% of dots, with 0.05 standard deviation is estimated 88% of dots and 94% with 0.06 standard deviation. Also it is defined, that linearity decrease is more than 5% when edge cut triangle which area is less then 10% of pixel area. Ill. 7, bibl. 6 (in English; summaries in English, Russian and Lithuanian).