Clustering and Classification of Images Using ABC-FCM and Naive Bayes Classifier
Abstract: This paper presents a hybrid clustering algorithm and Naive Bayes classifier for trees, shade, building and road. It starts with the single step preprocessing procedure to make the image suitable for clustering. The pre-processed image is clustered using the ABC-GA algorithm that is developed by hybridizing the ABC and genetic algorithm to obtain the effective clustering in satellite image and classified using Naive Bayes classifier. Classification accuracy of hybrid algorithm is found better than ABC.
Keywords: Clustering, classification, features extraction, Nave Bayes classifier, ABC-GA algorithm
How to Cite?: S. Praveena, "Clustering and Classification of Images Using ABC-FCM and Naive Bayes Classifier", Volume 5 Issue 6, June 2016, International Journal of Science and Research (IJSR), Pages: 2285-2288, https://www.ijsr.net/getabstract.php?paperid=ART201684, DOI: https://dx.doi.org/10.21275/ART201684