A Novel Hybrid CS-BFO Algorithm for Optimal Multilevel Image Thresholding Using Edge Magnitude Information

  • Sanjay AgrawalEmail author
  • Leena Samantaray
  • Rutuparna Panda


Thresholding is the key to simplify image classification. It becomes challenging when the number of thresholds is more than two. Most of the existing multilevel thresholding techniques use image histogram information (first-order statistics). This chapter utilizes optimal edge magnitude information (second-order statistics) of an image to obtain multilevel threshold values. We compute the edge magnitude information from the gray-level co-occurrence matrix (GLCM) of the image. The second-order statistics uses the correlation among the pixels for improved results. Maximization of edge magnitude is vital for obtaining optimal threshold values. The edge magnitude is maximized by introducing a novel hybrid cuckoo search-bacterial foraging optimization (CS-BFO) algorithm. The novelty of our proposed CS-BFO algorithm lies in its ability to provide improved chemotaxis in BFO algorithm, which is achieved by supplementing levy flight feature of CS. Social foraging models are relatively efficient for determining optimum multilevel threshold values. Hence, CS-BFO is used for improved thresholding performance and highlighting the novelty of this contribution. We have also implemented other soft computing tools cuckoo search (CS), particle swarm optimization (PSO), and genetic algorithm (GA) for a comparison. In addition, we have incorporated constraint handling in all the above-mentioned techniques so that optimal threshold values do not cross the bounds. This study reveals the fact that CS technique provides us improved speed while the CS-BFO method shows improved results both qualitatively and quantitatively.


Multilevel thresholding Edge magnitude GLCM Evolutionary computing 


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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Sanjay Agrawal
    • 1
    Email author
  • Leena Samantaray
    • 2
  • Rutuparna Panda
    • 1
  1. 1.VSS University of TechnologyBurlaIndia
  2. 2.Ajay Binay Institute of TechnologyCuttackIndia

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