Pattern Recognition
A survey of thresholding techniques
Computer Vision, Graphics, and Image Processing
Optimal thresholding—a new approach
Pattern Recognition Letters
Evolutionary computation: toward a new philosophy of machine intelligence
Evolutionary computation: toward a new philosophy of machine intelligence
A fast thresholding selection procedure for multimodal and unimodal histograms
Pattern Recognition Letters
A fast scheme for optimal thresholding using genetic algorithms
Signal Processing
The Performance Evaluation of Thresholding Algorithms for Optical character Recognition
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
A multi-level thresholding approach using a hybrid optimal estimation algorithm
Pattern Recognition Letters
Expert Systems with Applications: An International Journal
Optimal multi-level thresholding using a two-stage Otsu optimization approach
Pattern Recognition Letters
A new criterion for automatic multilevel thresholding
IEEE Transactions on Image Processing
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
The conventional multilevel thresholding methods are efficient for bi-level thresholding. However, they are computationally expensive extending to multilevel thresholding since they exhaustively search the optimal thresholds to optimize the objective functions. To overcome this drawback, a bacterial foraging (BF) algorithm based multilevel thresholding is presented in this paper. The BF algorithm is used to find the optimal threshold values for maximizing the Kapur's and Otsu's objective functions. The feasibility of the proposed BF technique has been tested on ten standard test images and benchmarked with particle swarm optimization algorithm (PSO) and genetic algorithm (GA). Experimental results of both qualitative and quantitative comparative studies for several existing methods illustrate the effectiveness and robustness of the proposed algorithm.