Saliency Cuts:
Salient Region Extraction based on Local Adaptive Thresholding for Image Information
Recognition of the Visually Impaired
Mukhriddin Mukhiddinov1, Rag-Gyo Jeong2, and Jinsoo Cho3
1Department of Hardware and Software of Control Systems in
Telecommunications, Tashkent University of Information Technologies named after
Muhammad al-Khwarizmi, Uzbekistan
2Korea Railroad Research Institute, Uiwang, Gyeonggi-do 16105, Republic of
Korea
3Department
of Computer Engineering, Gachon University, Republic of Korea
Abstract: In recent
years, there has been an increased scope for assistive software and
technologies, which help the visually impaired to perceive and recognize
natural scene images. In this article, we propose a novel saliency cuts
approach using local adaptive thresholding to obtain four regions from a given
saliency map. The saliency cuts approach is an effective tool for salient
object detection. First, we produce four regions for image segmentation using a
saliency map as an input image and applying an automatic threshold operation.
Second, the four regions are used to initialize an iterative version of the
Grab Cut algorithm and to produce a robust and high-quality binary mask with a
full resolution. Lastly, based on the binary mask and extracted salient object,
outer boundaries and internal edges are detected by Canny edge detection
method. Extensive experiments demonstrate that the proposed method correctly
detects and extracts the main contents of the image sequences for delivering
visually salient information to the visually impaired people compared to the
results of existing salient object segmentation algorithms.
Keywords: Saliency region
extraction, saliency map, saliency cuts,
local adaptive thresholding, the visually impaired.
Received February 7, 2018; accepted
January 6, 2020
https://doi.org/10.34028/iajit/17/5/4