An Exploration of Classification Approaches For Real Life Image Sets
Journal Title: International Journal of Engineering and Science Invention - Year 2017, Vol 6, Issue 12
Abstract
Classification is the imperative and challenging task in computer vision. Classification is based on description, texture or similarity of items or things. Image classification refers to the labeling of images into one of a number of predefined categories. Pixels are the unit represented in an image. Image classification is a process that understands the image and extracts the information that can be used for other tasks. The image classification process comprised of different phases as image acquisition, image pre-processing and image segmentation. Several classification techniques have been developed for classifying images. This paper presents a overview on various image classification techniques such as K-Nearest Neighbor (KNN), Support Vector Machine (SVM), classification and regression tree (CART),ADABOOST, K-Means, Naive Bayes, Decision Trees, ISODATA, Random Forest and DECORATE. Work done in the field of image classification has been presented in this paper. Various steps involved in the image classification process have also been discussed in the present paper.
Authors and Affiliations
Rajni Mehta, Sarbjeet Kaur Bath, Anuj Kumar Sharma
Keywords
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