A new multi-threshold image segmentation approach using state transition algorithm

Han, Jie; Yang, Chunhua; Zhou, Xiaojun; Gui, Weihua

doi:10.1016/j.apm.2017.02.015

Cited by 66 publications

(27 citation statements)

References 26 publications

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“…(1) Compared with Li's DRLSE model in [18], our proposed IRLS-IS model initializes the level set function to a constant, which solves the problem of selecting the initial size of the level set and is insensitive to the initialization. The IRLS-IS model can eliminate the dependence on this initial contour position so that it can segment images effectively.…”

Section: Discussionmentioning

confidence: 99%

“…As Gomes and Faugeras [58] revealed a disagreement between the theory and its implementation in the practical application of the level set method, a general scheme to solve these issues so far has not been obtained, and the process of the reinitialization is usually performed in a special manner. It is therefore necessary to investigate a new distance regularization term to avoid reinitialization [18].…”

Section: Chan Vese (Cv) Modelmentioning

confidence: 99%

“…Ananthi et al [17] investigated L-interval-valued intuitionistic fuzzy sets and set the least entropy as the threshold to segment the image. However, the method may lead to increased computation time, especially when dealing with multithreshold image segmentation [18]. Gao et al [19] introduced an enhanced artificial bee colony optimizer into multilevel threshold image segmentation.…”

Section: Introductionmentioning

confidence: 99%

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An Image Segmentation Method Based on Improved Regularized Level Set Model

Sun

Meng

et al. 2018

Applied Sciences

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When the level set algorithm is used to segment an image, the level set function must be initialized periodically to ensure that it remains a signed distance function (SDF). To avoid this defect, an improved regularized level set method-based image segmentation approach is presented. First, a new potential function is defined and introduced to reconstruct a new distance regularization term to solve this issue of periodically initializing the level set function. Second, by combining the distance regularization term with the internal and external energy terms, a new energy functional is developed. Then, the process of the new energy functional evolution is derived by using the calculus of variations and the steepest descent approach, and a partial differential equation is designed. Finally, an improved regularized level set-based image segmentation (IRLS-IS) method is proposed. Numerical experimental results demonstrate that the IRLS-IS method is not only effective and robust to segment noise and intensity-inhomogeneous images but can also analyze complex medical images well.

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Section: Discussionmentioning

confidence: 99%

Section: Chan Vese (Cv) Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An Image Segmentation Method Based on Improved Regularized Level Set Model

Sun

Meng

et al. 2018

Applied Sciences

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“…Algorithm. In recent years, state transition algorithm (STA) [19] as a novel stochastic intelligent algorithm for global optimization has been broadly applied to different fields, such as image segmentation [20], fractional-order PID controller tuning [21], copper removal and goethite process in the hydrometallurgical process of zinc [22,23], sensor network localization [24], and other fields [25,26]. The inspiration of STA is derived from the concepts of state and state transition.…”

Section: Modified State Transitionmentioning

confidence: 99%

An External Archive‐Based Constrained State Transition Algorithm for Optimal Power Dispatch

Zhou

Long

et al. 2019

Complexity

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This paper proposes an external archive-based constrained state transition algorithm (EA-CSTA) with a preference trade-off strategy for solving the power dispatch optimization problem in the electrochemical process of zinc (EPZ). The optimal power dispatch problem aims to obtain the optimal current density schedule to minimize the cost of power consumption with some rigorous technology and production constraints. The current density of each production equipment in different power stages is restricted by technology and production requirements. In addition, electricity price and current density are considered comprehensively to influence the cost of power consumption. In the process of optimization, technology and production restrictions are difficult to be satisfied, which are modeled as nonconvex equality constraints in the power dispatch optimization problem. Moreover, multiple production equipment and different power supply stages increase the amount of decision variables. In order to solve this problem, an external archive-based constrained state transition algorithm (EA-CSTA) is proposed. The external archive strategy is adopted for maintaining the diversity of solutions to increase the probability of finding the optima of power dispatch optimization problem. Moreover, a preference trade-off strategy is designed to improve the global search performance of EA-CSTA, and the translation transformation in state transition algorithm is modified to improve the local search ability of EA-CSTA. Finally, the experimental results indicate that the proposed method is more efficient compared with other approaches in previous papers for the optimal power dispatch. Furthermore, the proposed method significantly reduces the cost of power consumption, which not only guides the production process of zinc electrolysis but also alleviates the pressure of the power grid load.

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“…Currently, image extraction methods mainly include edge detection, threshold extraction [13,14], the clustering algorithm [15,16], saliency detection [17], and semantic segmentation [18]. Image extraction based on edge detection preserves the edge information of the input image by calculating the derivative between different pixels [19].…”

Section: Related Workmentioning

confidence: 99%

A Novel Extraction Method for Wildlife Monitoring Images with Wireless Multimedia Sensor Networks (WMSNs)

Liu

Wang

et al. 2019

Applied Sciences

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In remote areas, wireless multimedia sensor networks (WMSNs) have limited energy, and the data processing of wildlife monitoring images always suffers from energy consumption limitations. Generally, only part of each wildlife image is valuable. Therefore, the above mentioned issue could be avoided by transmitting the target area. Inspired by this transport strategy, in this paper, we propose an image extraction method with a low computational complexity, which can be adapted to extract the target area (i.e., the animal) and its background area according to the characteristics of the image pixels. Specifically, we first reconstruct a color space model via a CIELUV (LUV) color space framework to extract the color parameters. Next, according to the importance of the Hermite polynomial, a Hermite filter is utilized to extract the texture features, which ensures the accuracy of the split extraction of wildlife images. Then, an adaptive mean-shift algorithm is introduced to cluster texture features and color space information, realizing the extraction of the foreground area in the monitoring image. To verify the performance of the algorithm, a demonstration of the extraction of field-captured wildlife images is presented. Further, we conduct a comparative experiment with N-cuts (N-cuts), the existing aggregating super-pixels (SAS) algorithm, and the histogram contrast saliency detection (HCS) algorithm. A comparison of the results shows that the proposed algorithm for monitoring image target area extraction increased the average pixel accuracy by 11.25%, 5.46%, and 10.39%, respectively; improved the relative limit measurement accuracy by 1.83%, 5.28%, and 12.05%, respectively; and increased the average mean intersection over the union by 7.09%, 14.96%, and 19.14%, respectively.

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A new multi-threshold image segmentation approach using state transition algorithm

Cited by 66 publications

References 26 publications

An Image Segmentation Method Based on Improved Regularized Level Set Model

An Image Segmentation Method Based on Improved Regularized Level Set Model

An External Archive‐Based Constrained State Transition Algorithm for Optimal Power Dispatch

A Novel Extraction Method for Wildlife Monitoring Images with Wireless Multimedia Sensor Networks (WMSNs)

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