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S.Praveena; Dr.S.P.Singh (2015)
Publisher: International Journal of Engineering Research and Applications
Journal: International Journal of Engineering Research and Applications
Languages: English
Types: Article
Subjects: TA1-2040, Segmentation Algorithm, T, ABC-FCM, Feature Extraction, Satellite Image Classification, Engineering (General). Civil engineering (General), Technology, Neural Network

Classified by OpenAIRE into

ACM Ref: ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
This paper presents a hybrid clustering algorithm and feed-forward neural network classifier for land-cover mapping of trees, shade, building and road. It starts with the single step preprocessing procedure to make the image suitable for segmentation. The pre-processed image is segmented using the hybrid genetic-Artificial Bee Colony(ABC) algorithm that is developed by hybridizing the ABC and FCM to obtain the effective segmentation in satellite image and classified using neural network . The performance of the proposed hybrid algorithm is compared with the algorithms like, k-means, Fuzzy C means(FCM), Moving K-means, Artificial Bee Colony(ABC) algorithm, ABC-GA algorithm, Moving KFCM and KFCM algorithm.

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