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Robust Multi-thresholding in Noisy Grayscale Images Using Otsu’s Function and Harmony Search Optimization Algorithm

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Advances in Electronics, Communication and Computing

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 443))

Abstract

Multilevel segmentation in images clusters pixels depends on the total thresholds and intensity values. To find optimal thresholds and to maximize the objective function, entails a lot of computational power and memory. In this work gray-level segmentation is proposed by Otsu-based Harmonic Search Optimization Algorithm (HSOA) algorithm to resolve such drawbacks . The HS algorithm is employed to explore the optimum values of threshold by Otsu’s maximization objective function. Its effectiveness based on HS technique has been applied on 5 standard images with a size of 512 × 512. The images are associated with Gaussian (GN) and Salt-and-Pepper (SAP) noise. The measureable examination is performed with the parameters of between-class variance (Objective Function) value and quality measures, such as Root Mean Square Error (RMSE) and Peak Signal-to-Noise Ratio (PSNR). The experimental procedure is employed with MATLAB software. Experimental outcomes of Otsu-based harmony search offers an optimal solution to multilevel thresholding problem for the GN and SAP noise applied images with improved objective function and faster convergence.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Sathyabama University, Chennai, India

    K. Suresh

  2. St. Joseph’s College of Engineering, Chennai, 600119, India

    K. Suresh

  3. Department of Computer Science and Engineering, St. Joseph’s Institute of Technology, Chennai, 600119, India

    U. Sakthi

Authors
  1. K. Suresh
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  2. U. Sakthi
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Corresponding author

Correspondence to K. Suresh .

Editor information

Editors and Affiliations

  1. Smart Energy Research Unit, College of Engineering and Science, Victoria University, Melbourne, VIC, Australia

    Akhtar Kalam

  2. Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, West Bengal, India

    Swagatam Das

  3. Department of Computer Science and Engineering, Sikkim Manipal Institute of Technology, Rangpo, Sikkim, India

    Kalpana Sharma

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Suresh, K., Sakthi, U. (2018). Robust Multi-thresholding in Noisy Grayscale Images Using Otsu’s Function and Harmony Search Optimization Algorithm. In: Kalam, A., Das, S., Sharma, K. (eds) Advances in Electronics, Communication and Computing. Lecture Notes in Electrical Engineering, vol 443. Springer, Singapore. https://doi.org/10.1007/978-981-10-4765-7_52

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  • DOI: https://doi.org/10.1007/978-981-10-4765-7_52

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-4764-0

  • Online ISBN: 978-981-10-4765-7

  • eBook Packages: EngineeringEngineering (R0)

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