In this paper, we propose a multi-level thresholding model based on gray-level & local-
average histogram (GLLA) and Tsallis–Havrda–Charvát entropy for RGB color image. We …

The accuracy of brain tumor detection and segmentation are greatly affected by tumors'
location, shape, and image properties. In some situations, brain tumor detection and …

Infrared image segmentation is the basis of error detection for photovoltaic panels. In this
work, the infrared image data are collected by infrared thermal imager from the view of …

Water | Free Full-Text | Block-Greedy and CNN Based Underwater Image Dehazing for Novel
Depth Estimation and Optimal Ambient Light Next Article in Journal Evaluating the Landslide …

Image thresholding is one of the fastest and most effective methods of detecting objects in
infrared images. This paper proposes an infrared image thresholding method based on the …

The belt conveyor (BC) is the main means of horizontal transportation of bulk materials at
mining sites. The sudden fault in BC modules may cause unexpected stops in production …

The image thresholding methods consume a lot of time due to computational complexity
when the number of threshold levels increases. In order to reduce computation time and …

With the increase of the camera resolution, the number of pixels contained in froth image is
increased, which brings many challenges to image segmentation. Froth size and distribution …

An automatic thresholding method based on Shannon entropy difference and dynamic
synergic entropy is proposed to select a reasonable threshold from the gray level image with …

The utilization of automated techniques for processing and analyzing medical images can
offer significant support to doctors in their diagnostic and therapeutic practices. This study …