Fuzzy C-Means clustering algorithm for data with unequal cluster sizes and contaminated with noise and outliers: Review and development
S Askari - Expert Systems with Applications, 2021 - Elsevier
Clustering algorithms aim at finding dense regions of data based on similarities and
dissimilarities of data points. Noise and outliers contribute to the computational procedure of …
dissimilarities of data points. Noise and outliers contribute to the computational procedure of …
[PDF][PDF] A brief survey of color image preprocessing and segmentation techniques
S Bhattacharyya - Journal of Pattern Recognition Research, 2011 - Citeseer
Multichannel information processing from a diverse range of channel information is highly
time-and space-complex owing to the variety and enormity of underlying data. Most of the …
time-and space-complex owing to the variety and enormity of underlying data. Most of the …
Fast image-based obstacle detection from unmanned surface vehicles
M Kristan, VS Kenk, S Kovačič… - IEEE transactions on …, 2015 - ieeexplore.ieee.org
Obstacle detection plays an important role in unmanned surface vehicles (USVs). The USVs
operate in a highly diverse environments in which an obstacle may be a floating piece of …
operate in a highly diverse environments in which an obstacle may be a floating piece of …
Survey of contemporary trends in color image segmentation
In recent years, the acquisition of image and video information for processing, analysis,
understanding, and exploitation of the underlying content in various applications, ranging …
understanding, and exploitation of the underlying content in various applications, ranging …
A relay level set method for automatic image segmentation
This paper presents a new image segmentation method that applies an edge-based level
set method in a relay fashion. The proposed method segments an image in a series of …
set method in a relay fashion. The proposed method segments an image in a series of …
Quantum evolutionary clustering algorithm based on watershed applied to SAR image segmentation
The goal of segmentation is to partition an image into disjoint regions. In this paper, the
segmentation problem based on partition clustering is viewed as a combinatorial …
segmentation problem based on partition clustering is viewed as a combinatorial …
A framework of query expansion for image retrieval based on knowledge base and concept similarity
Y He, Y Li, J Lei, CHC Leung - Neurocomputing, 2016 - Elsevier
We study several semantic concept-based query expansion and re-ranking scheme and
compare different ontology-based expansion methods in image search and retrieval. To …
compare different ontology-based expansion methods in image search and retrieval. To …
Color image segmentation using morphological clustering and fusion with automatic scale selection
In this paper, a color image segmentation method considering pairwise color projections is
proposed. Each pairwise projection is analyzed according to an unsupervised …
proposed. Each pairwise projection is analyzed according to an unsupervised …
Noise-resistant fuzzy clustering algorithm
S Askari - Granular Computing, 2021 - Springer
The main objective of Fuzzy C-means (FCM) algorithm is to group data into some clusters
based on their similarities and dissimilarities. However, noise and outliers affect the …
based on their similarities and dissimilarities. However, noise and outliers affect the …
A customized Gabor filter for unsupervised color image segmentation
This paper presents work on accurate image segmentation utilizing local image
characteristics. Image features are measured by employing an appropriate Gabor filter with …
characteristics. Image features are measured by employing an appropriate Gabor filter with …