Soft computing approaches for image segmentation: a survey
Image segmentation is the method of partitioning an image into a group of pixels that are
homogenous in some manner. The homogeneity dependents on some attributes like …
homogenous in some manner. The homogeneity dependents on some attributes like …
Segmentation of images by color features: A survey
Image segmentation is an important stage for object recognition. Many methods have been
proposed in the last few years for grayscale and color images. In this paper, we present a …
proposed in the last few years for grayscale and color images. In this paper, we present a …
Image segmentation using computational intelligence techniques
Image segmentation methodology is a part of nearly all computer schemes as a pre-
processing phase to excerpt more meaningful and useful information for analysing the …
processing phase to excerpt more meaningful and useful information for analysing the …
Multilevel image threshold segmentation using an improved Bloch quantum artificial bee colony algorithm
F Huo, X Sun, W Ren - Multimedia Tools and Applications, 2020 - Springer
Multilevel threshold segmentation is one of the most broadly used image segmentation
methods. The key problem is how to obtain the optimal threshold as soon as possible. So a …
methods. The key problem is how to obtain the optimal threshold as soon as possible. So a …
Color image segmentation using genetic algorithm with aggregation-based clustering validity index (CVI)
Clustering validity index (CVI) plays an important role in data partitioning and image
segmentation. In this paper, a new CVI is proposed to perform the color image …
segmentation. In this paper, a new CVI is proposed to perform the color image …
Human-visual-perception-like intensity recognition for color rust images based on artificial neural network
HK Shen, PH Chen, LM Chang - Automation in Construction, 2018 - Elsevier
Digital image processing has been applied to the assessment of steel bridge coating quality
since the late 1990s. Most previously developed methods cluster rust images into two or …
since the late 1990s. Most previously developed methods cluster rust images into two or …
Categorical image retrieval through genetically optimized support vector machines (GOSVM) and hybrid texture features
Content-based image retrieval (CBIR) systems provide a potential solutions of retrieving
semantically similar images from large image repositories against any query image. The …
semantically similar images from large image repositories against any query image. The …
Evolving convolution neural network by optimal regularization random vector functional link for computational color constancy
J Yang, M Cai, Z Zhou - Optical Engineering, 2022 - spiedigitallibrary.org
To automatically eliminate the influence of external illumination on the acquired image,
restore the true color information of the object, and provide true and stable color features for …
restore the true color information of the object, and provide true and stable color features for …
Automatic computing of number of clusters for color image segmentation employing fuzzy c-means by extracting chromaticity features of colors
In this paper we introduce a method for color image segmentation by computing
automatically the number of clusters the data, pixels, are divided into using fuzzy c-means. In …
automatically the number of clusters the data, pixels, are divided into using fuzzy c-means. In …
C-means clustering fuzzified by two membership relative entropy functions approach incorporating local data information for noisy image segmentation
RR Gharieb, G Gendy, A Abdelfattah - Signal, Image and Video …, 2017 - Springer
In this paper, C-means algorithm is fuzzified and regularized by incorporating both local data
and membership information. The local membership information is incorporated via two …
and membership information. The local membership information is incorporated via two …