Image Multithresholding based on Kapur/Tsallis Entropy and Firefly Algorithm

Manic, K. Suresh; Priya, R. Krishna; Rajinikanth, V.

doi:10.17485/ijst/2016/v9i12/89949

Cited by 37 publications

(14 citation statements)

References 24 publications

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“…Another nonparametric method that is used to determine the optimal threshold values has been proposed by Kapur [15]. It is based on the entropy and the probability distribution of the image histogram.…”

Section: B Kapur Methodsmentioning

confidence: 99%

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Multilevel Thresholding for Image Segmentation Using an Improved Electromagnetism Optimization Algorithm

Hussein¹,

Mansour²,

Hussein³

2019

IJIMAI

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Image segmentation is considered one of the most important tasks in image processing, which has several applications in different areas such as; industry agriculture, medicine, etc. In this paper, we develop the electromagnetic optimization (EMO) algorithm based on levy function, EMO-levy, to enhance the EMO performance for determining the optimal multi-level thresholding of image segmentation. In general, EMO simulates the mechanism of attraction and repulsion between charges to develop the individuals of a population. EMO takes random samples from search space within the histogram of image, where, each sample represents each particle in EMO. The quality of each particle is assessed based on Otsu's or Kapur objective function value. The solutions are updated using EMO operators until determine the optimal objective functions. Finally, this approach produces segmented images with optimal values for the threshold and a few number of iterations. The proposed technique is validated using different standard test images. Experimental results prove the effectiveness and superiority of the proposed algorithm for image segmentation compared with well-known optimization methods.

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Section: B Kapur Methodsmentioning

confidence: 99%

“…Kapur method maximizes the entropy to measure the homogeneity of the classes [15]. The computational complexity of the two methods for multilevel thresholding is increasing for each new threshold [16].…”

Section: Introductionmentioning

confidence: 99%

Multilevel Thresholding for Image Segmentation Using an Improved Electromagnetism Optimization Algorithm

Hussein¹,

Mansour²,

Hussein³

2019

IJIMAI

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“…FA is a nature inspired meta-heuristic algorithm, in which flashing illumination patterns generated by fireflies are modeled using a suitable mathematical expression. In this work, the recent version of the FA discussed in [18][19][20] is considered.…”

Section: A Firefly Algorithmmentioning

confidence: 99%

Multi-loop PID Controller Design for Distillation Column using Firefly Algorithm

Saroja¹,

R²,

Meena³

et al. 2017

IJET

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Abstract-The main motivation of this manuscript is to develop a PID tuning procedure to improve the performance of the benchmark distillation column models using the heuristic firefly algorithm. A decentralised PID tuning approach is developed to design an independent PID controller for the top and bottom product loop. Minimization of a multi-objective function is chosen to guide the search process of the controller tuning procedure. The performance of the proposed approach is confirmed by evaluating the time domain parameters and the error values. From the experimental results, the main observation is that, proposed approach offers satisfactory result on the proposed approach and helps to achieve a reduced values of the time domain and error values. The proposed approach proves its efficiency in a benchmark Two Input Two Output (TITO) system. In future, this approach can be adopted to design controller for the multi-loop and non-linear systems existing in the process control literature. The proposed approach can also be compared against other heuristic approaches existing in the literature.

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“…Kapur's entropy is one of the procedures, widely used because of its dominance and elasticity. Kapur's entropy based multi-thresholding was largely discussed by the researchers to extract the important information from the RGB / gray scale test images [17][18][19][20][21]. This paper proposes a computer assisted technique to segment and analyze tumor from the brain MRI dataset.…”

Section: Introductionmentioning

confidence: 99%

“…Kapur's approach was initially proposed in 1985 [17]. The combination of Kapur's function and various heuristic algorithms has been presented over the past years for image thresholding applications [20,21].…”

Section: Introductionmentioning

confidence: 99%