Automatic Clustering Using Metaheuristic Algorithms for Content Based Image Retrieval
Publish place: Fifth International Conference on Electrical and Computer Engineering with Emphasis on Indigenous Knowledge
Publish Year: 1396
Type: Conference paper
Language: English
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Document National Code:
COMCONF05_330
Index date: 11 May 2018
Automatic Clustering Using Metaheuristic Algorithms for Content Based Image Retrieval abstract
Development of internet networks and mobile phone tools with image capturing capabilities and network connectivity within the recent years have led to defining new services and applications , using such tools. In this article, automatic clustering method using evolutionary and metaheuristic algorithms used in order to identify and categorize various kinds of digital images. For this purpose, a database of images prepared, and then k-means clustering method using evolutionary algorithms and optimization applied on these images. The results of retrieval indicate that automatic clustering using particle swarm optimization (PSO) algorithm has higher average retrieval accuracy in comparison with other methods
Automatic Clustering Using Metaheuristic Algorithms for Content Based Image Retrieval Keywords:
Image Retrieval , Feature Extraction , Automatic Clustering , Evolutionary and Metaheuristic Algorithms
Automatic Clustering Using Metaheuristic Algorithms for Content Based Image Retrieval authors
Javad Azarakhsh
Faculty of Marine Engineering, Chabahar Maritime University, Chabahar, Iran
Zobeir Raisi
Faculty of Marine Engineering, Chabahar Maritime University, Chabahar, Iran