Neural Computing and Applications

, Volume 29, Issue 12, pp 1285–1307 | Cite as

Multi-level image thresholding using Otsu and chaotic bat algorithm

  • Suresh Chandra Satapathy
  • N. Sri Madhava Raja
  • V. Rajinikanth
  • Amira S. AshourEmail author
  • Nilanjan Dey
Original Article


Multi-level thresholding is a helpful tool for several image segmentation applications. Evaluating the optimal thresholds can be applied using a widely adopted extensive scheme called Otsu’s thresholding. In the current work, bi-level and multi-level threshold procedures are proposed based on their histogram using Otsu’s between-class variance and a novel chaotic bat algorithm (CBA). Maximization of between-class variance function in Otsu technique is used as the objective function to obtain the optimum thresholds for the considered grayscale images. The proposed procedure is applied on a standard test images set of sizes (512 × 512) and (481 × 321). Further, the proposed approach performance is compared with heuristic procedures, such as particle swarm optimization, bacterial foraging optimization, firefly algorithm and bat algorithm. The evaluation assessment between the proposed and existing algorithms is conceded using evaluation metrics, namely root-mean-square error, peak signal to noise ratio, structural similarity index, objective function, and CPU time/iteration number of the optimization-based search. The results established that the proposed CBA provided better outcome for maximum number cases compared to its alternatives. Therefore, it can be applied in complex image processing such as automatic target recognition.


Multi-level thresholding Bat algorithm Otsu method Ikeda Map Peak signal to noise ratio (PSNR) Structural similarity index (SSIM) 


Compliance with ethical standards

Conflict of interest

We are the authors and confirm that there is no conflict of interest.


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Copyright information

© The Natural Computing Applications Forum 2016

Authors and Affiliations

  • Suresh Chandra Satapathy
    • 1
  • N. Sri Madhava Raja
    • 2
  • V. Rajinikanth
    • 2
  • Amira S. Ashour
    • 3
    Email author
  • Nilanjan Dey
    • 4
  1. 1.Department of Computer Science and EngineeringAnil Neerukonda Institute of Technology and SciencesVisakhapatnamIndia
  2. 2.Department of Electronics and Instrumentation EngineeringSt. Joseph’s College of EngineeringChennaiIndia
  3. 3.Department of Electronics and Electrical Communications Engineering, Faculty of EngineeringTanta UniversityTantaEgypt
  4. 4.Department of Information TechnologyTechno India College of TechnologyKolkataIndia

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