Open AccessPROPOSED METHOD FOR IMAGE SEGMENTATION USING GRAPH THEORY
Author(s) -
Balsam Hashim Kalleel,
Kadhim M. Hashim
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/928/3/032047
Subject(s) - segmentation , pixel , computer science , image segmentation , computation , graph , image (mathematics) , graph theory , vertex (graph theory) , artificial intelligence , binary number , binary image , cut , algorithm , segmentation based object categorization , block (permutation group theory) , pattern recognition (psychology) , scale space segmentation , mathematics , image processing , theoretical computer science , combinatorics , arithmetic
This paper presents an image segmentation technique using graph tools for object detection. Graph theoretical systems have many good features among different segmentation schemes. It organizes the image elements into mathematically and structural form, and makes the problem formulation more flexible, and the computation more efficient. In this paper, the work, consists of two stages, in the first stage we apply the pixel-based labeling algorithm to the binary image, the algorithm works similarly to the eight connectivity labeling, but it is broader than it in terms of the search area, where two (horizontal and vertical) thresholds are first defined so that the search is in a block whose height is the vertical threshold and its width (2 * horizontal threshold), in the second stage the output of the first stage is mapping into an undirected weighted graph, in which each vertex represent region rather than pixel. We evaluate the results by comparing it with other method using (RI) parameter. We use 50 image from online source and image taken from Berkeley database.