Tahereh Hassanzadeh - Faculty of IT and Computer EngineeringQazvin Azad University, Qazvin, IRAN
Hakimeh Vojodi
Amir Masoud Eftekhari Moghadam

Multilevel thresholding is an important techniquefor image processing. Many thresholding techniques havebeen proposed in the literature. Among them, the maximumentropy thresholding (MET) has been widely applied. In thispaper is presented a novel optimal multilevel thresholdingalgorithm based on maximum entropy measure and L´evyflightFirefly algorithm (LFA) for image segmentation. Thisnew method called, the maximum entropy based on L´evyflightFirefly algorithm for multilevel thresholding(MELFAMT) method. The proposed segmentation method isemployed for five benchmark images and the performancesobtained outperform results obtained with well-knownmethods, like Gaussian smoothing method, Symmetry-dualitymethod, improved GA-based algorithm, the hybridcooperative-comprehensive learning based PSO algorithm(HCOCLPSO)and A new social and momentum componentadaptive PSO algorithm (SMCAPSO) for image segmentation.

Image segmentation, L´evy-Flight Fireflyalgorithm, entropy, multilevel thresholding