Edge detection of binary images using the method of masks
This work addresses faster edge detection for binary images, but it appears incremental as it builds on existing mask-based techniques.
The paper tackled edge detection in binary images by using a method of masks with inverted image masks and binary operations, achieving a speed improvement of about 300 times faster than ordinary methods.
In this work the method of masks, creating and using of inverted image masks, together with binary operation of image data are used in edge detection of binary images, monochrome images, which yields about 300 times faster than ordinary methods. The method is divided into three stages: Mask construction, Fundamental edge detection, and Edge Construction Comparison with an ordinary method and a fuzzy based method is carried out.