Color Image Quantization: A Short Review and an Application with Artificial Bee Colony Algorithm

Informatica ◽  
2014 ◽  
Vol 25 (3) ◽  
pp. 485-503 ◽  
Author(s):  
Celal Ozturk ◽  
Emrah Hancer ◽  
Dervis Karaboga
Keyword(s):  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Color Image ◽  
Short Review ◽  
Bee Colony ◽  
Image Quantization

scholarly journals Color Image Quantization Based on the Artificial Bee Colony and Accelerated K-means Algorithms

Symmetry ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 1222
Author(s):  
Shu-Chien Huang
Keyword(s):  
Artificial Bee Colony ◽  
Color Image ◽  
Search Algorithm ◽  
Computation Time ◽  
Color Palette ◽  
Bee Colony ◽  
Image Quantization ◽  
Important Approach ◽  
Three Stages ◽  
Color Pixel

Color image quantization techniques have been widely used as an important approach in color image processing and data compression. The key to color image quantization is a good color palette. A new method for color image quantization is proposed in this study. The method consists of three stages. The first stage is to generate N colors based on 3D histogram computation, the second is to obtain the initial palette by selecting K colors from the N colors based on an artificial bee colony algorithm, and the third is to obtain the quantized images using the accelerated K-means algorithm. In order to reduce the computation time, the sampling process is employed. The closest color in the palette for each sampled color pixel in the color image is efficiently determined by the mean-distance-ordered partial codebook search algorithm. The experimental results show that the proposed method can generate high-quality quantized images with less time consumption.

Path Planning of Mobile Robot Using Improved Artificial Bee Colony Algorithm

2020 ◽  
Vol 38 (9A) ◽  
pp. 1384-1395
Author(s):  
Rakaa T. Kamil ◽  
Mohamed J. Mohamed ◽  
Bashra K. Oleiwi
Keyword(s):  
Mobile Robot ◽  
Comparative Research ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Dynamic Control ◽  
Computational Time ◽  
Bee Colony ◽  
Shortest Distance ◽  
Minimum Number ◽  
Cubic Polynomial

A modified version of the artificial Bee Colony Algorithm (ABC) was suggested namely Adaptive Dimension Limit- Artificial Bee Colony Algorithm (ADL-ABC). To determine the optimum global path for mobile robot that satisfies the chosen criteria for shortest distance and collision–free with circular shaped static obstacles on robot environment. The cubic polynomial connects the start point to the end point through three via points used, so the generated paths are smooth and achievable by the robot. Two case studies (or scenarios) are presented in this task and comparative research (or study) is adopted between two algorithm’s results in order to evaluate the performance of the suggested algorithm. The results of the simulation showed that modified parameter (dynamic control limit) is avoiding static number of limit which excludes unnecessary Iteration, so it can find solution with minimum number of iterations and less computational time. From tables of result if there is an equal distance along the path such as in case A (14.490, 14.459) unit, there will be a reduction in time approximately to halve at percentage 5%.

Artificial bee colony algorithm with modified search strategy

2013 ◽  
Vol 32 (12) ◽  
pp. 3326-3330
Author(s):  
Yin-xue ZHANG ◽  
Xue-min TIAN ◽  
Yu-ping CAO
Keyword(s):  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Search Strategy ◽  
Bee Colony
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