Increased Accuracy in Image Segmentation Considering the Modular Method Based on Texture Characteristics and Super Pixel

Abstract

To solve the problem of segmenting an image into homogeneous regions with large area, this paper proposes an efficient algorithm that is based optimization base on modularity and super pixel method. Due to the fact that a very small areas of the image before segmentation, the proposed algorithm automatically merged with neighboring small areas and to make larger modules. When the modularity pictures after the merger to reach its maximum stop, leading to the production of segmentation algorithms are final. To keep repetitive patterns in a homogeneous area, a feature based on its histogram modularity with features like color and eventually identified two areas by creating a similarity matrix, it is suggested. So that the problem of segmentation and complexity of the problem to some extent eliminate in a way that due to the combined areas can be achieved for repetitive patterns. Simulation results show that the algorithm has good accuracy.