An Effective Multilevel Thresholding Approach Using Conditional Probability Entropy and Genetic Algorithm
نویسندگان
چکیده
Entropy-based image thresholding are used widely in image processing. Conventional methods are efficient in the case of bilevel thresholding. But they are very computationally time consuming when extended to multilevel thresholding since they exhaustively search the optimal thresholds to optimize the objective functions. In this paper, we propose a conditional probability entropy (CPE) based on Bayesian theory and employ Genetic Algorithm (GA) to maximize the CPE for the multithresholds. The experimental results show that CPE is a good criterion of image thresholding and GA is a applicable fast algorithm for multi-level thresholding compared to the exhaustive searching method.
منابع مشابه
A Hierarchical Approach in Multilevel Thresholding Based on Maximum Entropy and Bayes' Formula
An efficient hierarchical approach for image multi-level thresholding is proposed based on the maximum entropy principle and Bayes’ formula, in which no assumptions of the image histogram are made. Five forms of conditional probability distributions are employed for optimal threshold determination. Our experiments demonstrate that the proposed method is effective and achieves a significant impr...
متن کاملColor Image Segmentation and Multi-Level Thresholding by Maximization of Conditional Entropy
In this work a novel approach for color image segmentation using higher order entropy as a textural feature for determination of thresholds over a two dimensional image histogram is discussed. A similar approach is applied to achieve multi-level thresholding in both grayscale and color images. The paper discusses two methods of color image segmentation using RGB space as the standard processing...
متن کاملOptimal Multi-Level Thresholding Based on Maximum Tsallis Entropy via an Artificial Bee Colony Approach
This paper proposes a global multi-level thresholding method for image segmentation. As a criterion for this, the traditional method uses the Shannon entropy, originated from information theory, considering the gray level image histogram as a probability distribution, while we applied the Tsallis entropy as a general information theory entropy formalism. For the algorithm, we used the artificia...
متن کاملCuckoo search algorithm and wind driven optimization based study of satellite image segmentation for multilevel thresholding using Kapur's entropy
The objective of image segmentation is to extract meaningful objects. A meaningful segmentation selects the proper threshold values to optimize a criterion using entropy. The conventional multilevel thresholding methods are efficient for bi-level thresholding. However, they are computationally expensive when extended to multilevel thresholding since they exhaustively search the optimal threshol...
متن کاملMultilevel edge detection using quantum and classical genetic algorithms: A comparative study
In this work, we develop a multilevel edge detection method based on the Kapur and Tsallis entropies. The multilevel thresholding approach gives rise to an NP-hard optimization problem. We have used the Classical Genetic Algorithm (CGA) and the Quantum Genetic Algorithm (QGA) to solve this problem. The performance of the QGA has been tested on ten sample images and it is shown that the QGA outp...
متن کامل