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Digital Image Classification Techniques: A Comprehensive Review

Digital Image Classification Techniques: A Comprehensive Review

Utkarsh Shrivastav, Sanjay Kumar Singh
Copyright: © 2019 |Pages: 26
ISBN13: 9781522590965|ISBN10: 152259096X|ISBN13 Softcover: 9781522590996|EISBN13: 9781522590972
DOI: 10.4018/978-1-5225-9096-5.ch009
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MLA

Shrivastav, Utkarsh, and Sanjay Kumar Singh. "Digital Image Classification Techniques: A Comprehensive Review." Hidden Link Prediction in Stochastic Social Networks, edited by Babita Pandey and Aditya Khamparia, IGI Global, 2019, pp. 162-187. https://doi.org/10.4018/978-1-5225-9096-5.ch009

APA

Shrivastav, U. & Singh, S. K. (2019). Digital Image Classification Techniques: A Comprehensive Review. In B. Pandey & A. Khamparia (Eds.), Hidden Link Prediction in Stochastic Social Networks (pp. 162-187). IGI Global. https://doi.org/10.4018/978-1-5225-9096-5.ch009

Chicago

Shrivastav, Utkarsh, and Sanjay Kumar Singh. "Digital Image Classification Techniques: A Comprehensive Review." In Hidden Link Prediction in Stochastic Social Networks, edited by Babita Pandey and Aditya Khamparia, 162-187. Hershey, PA: IGI Global, 2019. https://doi.org/10.4018/978-1-5225-9096-5.ch009

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Abstract

Image classification is a technique to categorize an image in to given classes on the basis of hidden characteristics or features extracted using image processing. With rapidly growing technology, the size of images is growing. Different categories of images may contain different types of hidden information such as x-ray, CT scan, MRI, pathologies images, remote sensing images, satellite images, and natural scene image captured via digital cameras. In this chapter, the authors have surveyed various articles and books and summarized image classification techniques. There are supervised techniques like KNN and SVM, which classify an image into given classes and unsupervised techniques like K-means and ISODATA for classifying image into a group of clusters. For big images, deep learning networks can be employed that are fast and efficient and also compute hidden features automatically.

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