Abstract
In this paper, a multilevel thresholding (MT) algorithm based on the harmony search algorithm (HSA) is introduced. HSA is an evolutionary method which is inspired in musicians improvising new harmonies while playing. Different to other evolutionary algorithms, HSA exhibits interesting search capabilities still keeping a low computational overhead. The proposed algorithm encodes random samples from a feasible search space inside the image histogram as candidate solutions, whereas their quality is evaluated considering the objective functions that are employed by the Otsu’s or Kapur’s methods. Guided by these objective values, the set of candidate solutions are evolved through the HSA operators until an optimal solution is found. Experimental results demonstrate the high performance of the proposed method for the segmentation of digital images.
Highlights
Segmentation is one of the most important tasks in image processing that endeavors to identify whether a pixel intensity corresponds to a predefined class
In order to maintain compatibility with similar works reported in the literature [14, 15, 18, 19], the number of thresholds points used in the test are th = 2, 3, 4, 5
The approach combines the good search capabilities of harmony search algorithm (HSA) algorithm and the use of some objective functions that have been proposed by the popular multilevel thresholding (MT) methods of Otsu and Kapur
Summary
Segmentation is one of the most important tasks in image processing that endeavors to identify whether a pixel intensity corresponds to a predefined class. In recent years image processing has been applied to different areas as engineering, medicine, agriculture, and so forth. The TH nonparametric employs several criteria such as the between-class variance, the entropy, and the error rate [6,7,8] in order to verify the quality of a th value. These metrics could be used as optimization functions since they result as an attractive option due their robustness and accuracy
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
