In this paper, we investigate the ability of two new nature-inspired metaheuristics namely the
flower pollination (FP) and the social spiders optimization (SSO) algorithms to solve the …

Image segmentation is a key stage in image processing because it simplifies the
representation of the image and facilitates subsequent analysis. The multi-level thresholding …

A new multilevel thresholding based image segmentation technique is developed which
utilizes Masi entropy as an objective function. Thresholding is an important image …

Image segmentation is considered a crucial step required for image analysis and research.
Many techniques have been proposed to resolve the existing problems and improve the …

Image segmentation is an essential part of image analysis, which has a direct impact on the
quality of image analysis results. Thresholding is one of the simplest and widely used …

Multilevel thresholding is one of the most popular image segmentation techniques. In order
to determine the thresholds, most methods use the histogram of the image. This paper …

Multilevel thresholding is an important technique for image processing and pattern
recognition. The maximum entropy thresholding (MET) has been widely applied in the …

Image segmentation is a fundamental but essential step in image processing because it
dramatically influences posterior image analysis. Multilevel thresholding image …

In this paper, a modified artificial bee colony (MABC) algorithm based satellite image
segmentation using different objective function has been presented to find the optimal …

Multilevel-thresholding is an efficient method used in image segmentation. This paper
presents a hybrid meta-heuristic approach for multi-level thresholding image segmentation …