TITLE

Optimal Multilevel Image Thresholding: An Analysis with PSO and BFO Algorithms

AUTHOR(S)
Rajinikanth, V.; Raja, N. Sri Madhava; Latha, K.
PUB. DATE
June 2014
SOURCE
Australian Journal of Basic & Applied Sciences;Jun2014, Vol. 8 Issue 9, p443
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
Multilevel thresholding is widely adopted in image processing and pattern recognition fields. In this paper, Otsu based bi-level and multi-level image segmentation problem is addressed using Particle Swarm Optimization (PSO) and Bacterial Foraging Optimization (BFO) algorithms. Optimal thresholds are attained by analyzing histogram of the test image. Maximization of Otsu's between class variance function is adopted to guide the heuristic algorithm based exploration. Performance of the proposed method is tested on eight benchmark test images using various numbers of thresholds. An assessment between PSO (constant weight), PSO (varying weight), Adaptive BFO, and Enhanced BFO are performed and the experimental results are validated using well known statistical parameters. For a bi-level optimization problem, considered heuristic algorithms show equal performance. For increase in threshold levels, PSO (constant weight) offers faster convergence and Enhanced BFO provides better structural similarity (SSIM) index.
ACCESSION #
97368447

 

Related Articles

  • Multilevel Thresholding using PSO Clustering. Dash, Prasannajit; Nayak, Maya // International Journal of Computer Applications;Jul2014, Vol. 97, p27 

    Thresholding algorithms are quite easy and effective for bi-level thresholding but in case of multilevel thresholding, the performance becomes unreliable due to complexity in computation because the complexity will exponentially increase. In this approach, multilevel thresholding is done for...

  • Research on Image Segmentation Algorithms based on Particle Swarm Optimization and Neural Network. LI Fengling // Journal of Convergence Information Technology;Sep2012, Vol. 7 Issue 16, p409 

    In order to segment cells image better, this paper modifies traditional BP neural network: first, set afferent neuron as a 3*3 window to replace traditional one pixel channel; second, apply a method based on comentropy to estimate the number of hidden neurons; at last, apply an improved PSO...

  • Combining Clustering, Morphology and Metaheuristic Optimization Technique for Segmentation of Breast Ultrasound Images to Detect Tumors. Prabusankarlal, K. M.; Thirumoorthy, P.; Manavalan, R. // International Journal of Computer Applications;Jan2014, Vol. 86, p28 

    A framework which combines morphological operations and metaheuristic optimization technique with clustering method for the precise segmentation of breast tumours using ultrasound images is proposed in this study. Malignant tumours are pernicious when neglected to detect and treat at the...

  • A neighbourhood property for the job shop scheduling problem with application to hybrid particle swarm optimization. Zhang, Rui; Wu, Cheng // IMA Journal of Management Mathematics;Jan2013, Vol. 24 Issue 1, p111 

    The job shop scheduling problem (JSSP) is a notoriously difficult problem in combinatorial optimization. Up till now, neighbourhood search has been the most efficient optimization framework for solving the problem. The discovery and innovative application of neighbourhood properties is a key...

  • Discrete Particle Swarm Optimization for the minimum labelling Steiner tree problem. Consoli, Sergio; Moreno-Pe´rez, José Andrés; Darby-Dowman, Kenneth; Mladenović, Nenad // Natural Computing;Mar2010, Vol. 9 Issue 1, p29 

    Particle Swarm Optimization is a population-based method inspired by the social behaviour of individuals inside swarms in nature. Solutions of the problem are modelled as members of the swarm which fly in the solution space. The improvement of the swarm is obtained from the continuous movement...

  • A Hybrid Approach Using Particle Swarm Optimization and Simulated Annealing for N-queen Problem. Saffarzadeh, Vahid Mohammadi; Jafarzadeh, Pourya; Mazloom, Masoud // World Academy of Science, Engineering & Technology;Jul2010, Issue 43, p974 

    No abstract available.

  • An Efficient Hybrid Genetic Algorithm for Performance Enhancement in solving Travelling Salesman Problem. Dalip, Navjot Kaur // International Journal on Computer Science & Engineering;2011, Vol. 3 Issue 11, p3502 

    This paper, proposes a solution for Travelling Salesman Problem (TSP) [1], using Genetic Algorithm (GA). The proposed algorithm works on data sets of latitude and longitude coordinates of cities and provides optimal tours in shorter time; giving convergence that is fast and better. To improve...

  • A new approach to dual channel speech enhancement based on gravitational search algorithm (GSA). Prajna, K.; Rao, G.; Reddy, K.; Maheswari, R. // International Journal of Speech Technology;Dec2014, Vol. 17 Issue 4, p341 

    This paper proposes novel heuristic algorithm called gravitational search algorithm (GSA) to speech enhancement. Stochastic and heuristic algorithms like particle swarm optimization (PSO) and some of its variants have been adapted to the field of speech enhancement in recent years. Although...

  • Vehicle Routing Problem Based on Heuristic Artificial Fish School Algorithm. Lei Qin; Yaqin Li; Kang Zhou // Applied Mechanics & Materials;2014, Vol. 721, p56 

    Vehicle Routing Problem (VRP) is one of the core issue of logistics distribution, for traditional precision algorithms and heuristic algorithms had low accuracies or easily fell into local optimal solutions, it was difficult to obtain the optimal solution. This paper proposes a heuristic...

Share

Read the Article

Courtesy of THE LIBRARY OF VIRGINIA

Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics