Volume 13 (2025)
Volume 12 (2024)
Volume 11 (2023)
Volume 10 (2022)
Volume 9 (2021)
Volume 8 (2020)
Volume 7 (2019)
Volume 6 (2018)
Volume 5 (2017)
Volume 4 (2016)
Volume 3 (2015)
Volume 2 (2014)
Volume 1 (2013)
H.5.7. Segmentation
Fuzzy Clustering of Noisy Images Using a Gaussian Kernel and Spatial Information with Automatic Parameter Tuning and C+ Means Initialization

Mohsen Erfani Haji Pour

Volume 12, Issue 4 , November 2024, , Pages 497-510

https://doi.org/10.22044/jadm.2024.15043.2606

Abstract
  The segmentation of noisy images remains one of the primary challenges in image processing. Traditional fuzzy clustering algorithms often exhibit poor performance in the presence of high-density noise due to insufficient consideration of spatial features. In this paper, a novel approach is proposed that ...  Read More

H.5.7. Segmentation
Enhancing Image Segmentation with Darwinian Grey Wolf Optimizer: A Novel Multilevel Thresholding Approach

Ehsan Ehsaeyan

Volume 12, Issue 2 , April 2024, , Pages 217-225

https://doi.org/10.22044/jadm.2024.14469.2550

Abstract
  This paper presents a novel approach to image segmentation through multilevel thresholding, leveraging the speed and precision of the technique. The proposed algorithm, based on the Grey Wolf Optimizer (GWO), integrates Darwinian principles to address the common stagnation issue in metaheuristic algorithms, ...  Read More

H.5.7. Segmentation
Image Segmentation using Improved Imperialist Competitive Algorithm and a Simple Post-processing

V. Naghashi; Sh. Lotfi

Volume 7, Issue 4 , November 2019, , Pages 507-519

https://doi.org/10.22044/jadm.2019.3935.1464

Abstract
  Image segmentation is a fundamental step in many of image processing applications. In most cases the image’s pixels are clustered only based on the pixels’ intensity or color information and neither spatial nor neighborhood information of pixels is used in the clustering process. Considering ...  Read More