Hybrid Data Mining Approach for Image Segmentation Based Classification

2016 ◽  
Vol 3 (2) ◽  
pp. 65-81 ◽  
Author(s):  
Mrutyunjaya Panda ◽  
Aboul Ella Hassanien ◽  
Ajith Abraham
Keyword(s):  
Neural Network ◽  
Data Mining ◽  
Image Segmentation ◽  
Search Algorithm ◽  
Rbf Neural Network ◽  
Harmony Search ◽  
Optimal Solution ◽  
Solution Space ◽  
Feature Subset ◽  
Data Mining Technique

Evolutionary harmony search algorithm is used for its capability in finding solution space both locally and globally. In contrast, Wavelet based feature selection, for its ability to provide localized frequency information about a function of a signal, makes it a promising one for efficient classification. Research in this direction states that wavelet based neural network may be trapped to fall in a local minima whereas fuzzy harmony search based algorithm effectively addresses that problem and able to get a near optimal solution. In this, a hybrid wavelet based radial basis function (RBF) neural network (WRBF) and feature subset harmony search based fuzzy discernibility classifier (HSFD) approaches are proposed as a data mining technique for image segmentation based classification. In this paper, the authors use Lena RGB image; Magnetic resonance image (MR) and Computed Tomography (CT) Image for analysis. It is observed from the obtained simulation results that Wavelet based RBF neural network outperforms the harmony search based fuzzy discernibility classifiers.

Hybrid Data Mining Approach for Image Segmentation Based Classification

Biometrics ◽  
2017 ◽  
pp. 1543-1561 ◽  
Author(s):  
Mrutyunjaya Panda ◽  
Aboul Ella Hassanien ◽  
Ajith Abraham
Keyword(s):  
Neural Network ◽  
Data Mining ◽  
Image Segmentation ◽  
Search Algorithm ◽  
Rbf Neural Network ◽  
Harmony Search ◽  
Optimal Solution ◽  
Solution Space ◽  
Harmony Search Algorithm ◽  
Data Mining Technique

Evolutionary harmony search algorithm is used for its capability in finding solution space both locally and globally. In contrast, Wavelet based feature selection, for its ability to provide localized frequency information about a function of a signal, makes it a promising one for efficient classification. Research in this direction states that wavelet based neural network may be trapped to fall in a local minima whereas fuzzy harmony search based algorithm effectively addresses that problem and able to get a near optimal solution. In this, a hybrid wavelet based radial basis function (RBF) neural network (WRBF) and feature subset harmony search based fuzzy discernibility classifier (HSFD) approaches are proposed as a data mining technique for image segmentation based classification. In this paper, the authors use Lena RGB image; Magnetic resonance image (MR) and Computed Tomography (CT) Image for analysis. It is observed from the obtained simulation results that Wavelet based RBF neural network outperforms the harmony search based fuzzy discernibility classifiers.

Aquatic Image Segmentation Method Based on HS-PCNN for Automatic Operation Boat in Crab Farming

2016 ◽  
Vol 13 (10) ◽  
pp. 7366-7374 ◽  
Author(s):  
Chengzhi Ruan ◽  
Dean Zhao ◽  
Xu Chen ◽  
Weikuan Jia ◽  
Xiaoyang Liu
Keyword(s):  
Neural Network ◽  
Image Segmentation ◽  
Search Algorithm ◽  
Harmony Search ◽  
Yield Function ◽  
Difficult Problem ◽  
Visual Navigation ◽  
Production Costs ◽  
Operating Efficiency ◽  
Pulse Coupled Neural Network

Crab farming mainly adopts the pattern of aquatic feeding, which is a hard work for farmers. To reduce the labor intensity and production costs for farmers, it is great significance to develop an automatic aquatic-cleaning boat with visual navigation. In visual navigation system, image segmentation is a difficult problem. In this paper, we combine the advantages of pulse coupled neural network in image segmentation with the global optimization characteristic of harmony search algorithm, an image segmentation algorithm of optimized pulse coupled neural network based on harmony search (HS-PCNN) is proposed. In order to improve the operating efficiency and segmentation accuracy of PCNN, this new algorithm can optimize the weighted combination of PCNN maximum Shannon entropy and minimum cross entropy by harmony search (HS), and evaluate the optimization effect of parameters by using yield function. Experimental results show that the proposed method can provide a more effective method for the aquatic image segmentation in crab pond.

scholarly journals Techniques for Image Segmentation: A Critical Review

2021 ◽  
Vol 9 (3) ◽  
pp. 1-4
Author(s):  
Harshita Mishra ◽  
Anuradha Misra
Keyword(s):  
Data Mining ◽  
Image Processing ◽  
Image Segmentation ◽  
Digital Image ◽  
Electronic Devices ◽  
Data Mining Technique ◽  
Mining Technique ◽  
Mathematical Algorithms ◽  
Picture Element

In today’s world there is requirement of some techniques or methods that will be helpful for retrieval of the information from the images. Information those are important for finding solution to the problems in the present time are needed. In this review we will study the processing involved in the digitalization of the image. The set or proper array of the pixels that is also called as picture element is known as image. The positioning of these pixels is in matrix which is formed in columns and rows. The image undergoes the process of digitalization by which a digital image is formed. This process of digitalization is called digital image processing of the image (D.I.P). Electronic devices as such computers are used for the processing of the image into digital image. There are various techniques that are used for image segmentation process. In this review we will also try to understand the involvement of data mining for the extraction of the information from the image. The process of the identifying patterns in the large stored data with the help of statistic and mathematical algorithms is data mining. The pixel wise classification of the image segmentation uses data mining technique.

scholarly journals Hybrid Multilevel Thresholding and Improved Harmony Search Algorithm for Segmentation

2018 ◽  
Vol 8 (6) ◽  
pp. 4593 ◽  
Author(s):  
Erwin Erwin ◽  
Saparudin Saparudin ◽  
Wulandari Saputri
Keyword(s):  
High Performance ◽  
Search Algorithm ◽  
Signal To Noise Ratio ◽  
Harmony Search ◽  
Optimal Solution ◽  
Harmony Search Algorithm ◽  
Multilevel Thresholding ◽  
Improved Harmony Search ◽  
High Degree ◽  
Improved Harmony Search Algorithm

This paper proposes a new method for image segmentation is hybrid multilevel thresholding and improved harmony search algorithm. Improved harmony search algorithm which is a method for finding vector solutions by increasing its accuracy. The proposed method looks for a random candidate solution, then its quality is evaluated through the Otsu objective function. Furthermore, the operator continues to evolve the solution candidate circuit until the optimal solution is found. The dataset used in this study is the retina dataset, tongue, lenna, baboon, and cameraman. The experimental results show that this method produces the high performance as seen from peak signal-to-noise ratio analysis (PNSR). The PNSR result for retinal image averaged 40.342 dB while for the average tongue image 35.340 dB. For lenna, baboon and cameramen produce an average of 33.781 dB, 33.499 dB, and 34.869 dB. Furthermore, the process of object recognition and identification is expected to use this method to produce a high degree of accuracy.

Optimal hybrid scheme of dynamic neural network and PID controller based on harmony search algorithm to control a PWM-driven pneumatic actuator position

2017 ◽  
Vol 24 (16) ◽  
pp. 3538-3554 ◽  
Author(s):  
Mahmood Mazare ◽  
Mostafa Taghizadeh ◽  
Mohammad Ghasem Kazemi
Keyword(s):  
Neural Network ◽  
Pid Controller ◽  
Pulse Width Modulation ◽  
Search Algorithm ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Pneumatic Actuator ◽  
Hybrid Scheme ◽  
Dynamic Neural Network ◽  
Switching Valve

In this paper, the position of a pulse width modulation (PWM)-driven pneumatic actuator has been controlled using a dynamic neural network (DNN) and Proportional Integral Derivative (PID) controller. The harmony search algorithm (HSA) has been used to unravel the optimization problem. The DNN controller is optimally designed to control the position of the actuator. As to the performance of the PID controller, it can assist the DNN controller to give better results. Therefore, an optimal hybrid scheme with both DNN and PID controllers based on HSA is suggested. A pneumatic circuit containing a fast-switching valve is used to reduce the complexity of the PWM-driven servo pneumatic system along with its cost price.

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