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Image Binarization by Dynamic Convex Quadrilateral Region Segmentation Using GA
Author(s) -
NAKAMURA SOMA,
SAITOH FUMIHIKO
Publication year - 2016
Publication title -
electronics and communications in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.131
H-Index - 13
eISSN - 1942-9541
pISSN - 1942-9533
DOI - 10.1002/ecj.11775
Subject(s) - thresholding , artificial intelligence , binary image , computer vision , image (mathematics) , image segmentation , diagonal , quadrilateral , image processing , computer science , feature detection (computer vision) , pattern recognition (psychology) , binary number , image gradient , noise (video) , mathematics , engineering , geometry , finite element method , arithmetic , structural engineering
SUMMARY The method that binarizes an image by local thresholds in separated image areas is useful when the image has uneven brightness. A method was proposed to separate an image dynamically for local thresholding to generate a binary image by using a genetic algorithm (GA). However, the existing method used only horizontal and vertical lines for image separation. This paper suggests a method of separating an image dynamically using diagonal lines for local thresholding in order to generate a binary image by using a GA and of evaluating binary images. The experimental results show that the images binarized by the proposed method have good separation of objects from the background, and that they include less noise and blur than those binarized by the existing method.