Multilevel minimum cross entropy threshold selection based on the honey bee mating optimization
نویسندگان
چکیده
منابع مشابه
Multilevel minimum cross entropy threshold selection based on the honey bee mating optimization
Image entropy thresholding approach has drawn the attentions in image segmatation. The endeavor of this paper is focused on multilevel thresholding using the minimum cross enrtop criterion. In the literature, the particle swarm optimization (PSO) had been applied to conducting the thresold selection. The adopted algorithm used in this paper is the honey bee mating optimization (HBMO). In experi...
متن کاملMultilevel minimum cross entropy threshold selection based on particle swarm optimization
Thresholding is one of the popular and fundamental techniques for conducting image segmentation. Many thresholding techniques have been proposed in the literature. Among them, the minimum cross entropy thresholding (MCET) have been widely adopted. Although the MCET method is effective in the bilevel thresholding case, it could be very time-consuming in the multilevel thresholding scenario for m...
متن کاملMultilevel Minimum Cross Entropy Thresholding using Artificial Bee Colony Algorithm
The minimum cross entropy thresholding (MCET) has been widely applied in image processing. In this paper, a new multilevel MCET algorithm based on the artificial bee colony (ABC) algorithm is proposed. The proposed thresholding algorithm is called ABC-based MCET algorithm. Four different methods including the exhaustive search, the honey bee mating optimization (HBMO), the particle swarm optimi...
متن کاملApplication of honey-bee mating optimization algorithm on clustering
Cluster analysis is one of attractive data mining technique that use in many fields. One popular class of data clustering algorithms is the center based clustering algorithm. K-means used as a popular clustering method due to its simplicity and high speed in clustering large datasets. However, K-means has two shortcomings: dependency on the initial state and convergence to local optima and glob...
متن کاملAn improved scheme for minimum cross entropy threshold selection based on genetic algorithm
0950-7051/$ see front matter 2011 Elsevier B.V. A doi:10.1016/j.knosys.2011.02.013 ⇑ Corresponding author. E-mail address: [email protected] (K. Tang). Image segmentation is one of the most critical tasks in image analysis. Thresholding is definitely one of the most popular segmentation approaches. Among thresholding methods, minimum cross entropy thresholding (MCET) has been widely adopted fo...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Expert Systems with Applications
سال: 2010
ISSN: 0957-4174
DOI: 10.1016/j.eswa.2009.12.050