Citation :

S.Saravanan, A.K.Ashfauk Ahamed, "A Novel Framework for Content Classification Process of Online Newspaper Images Using Deep Learning Algorithm," International Journal of Engineering Trends and Technology (IJETT), vol. 74, no. 9, pp. 333-348, 2026. Crossref, https://doi.org/10.14445/22315381/IJETT-V74I9P123

Abstract

This paper develops an image processing-based system in order to verify the contents in each online newspaper. The newspaper contains many sub articles under various headings. Each sub articles in the newspaper may corresponds to various social activities such as Crime, Education, Sports, Politics, Entertainment and Culture. In this work, a newspaper word classification system has been proposed using Deep Learning architecture. This proposed system consists of a preprocessing section, Deep Learning (DL) Architectural module and a data retrieval algorithm. The preprocessing section is used in this work to convert the spatial image into frequency translational image by Gabor transform, and further, Optical Character Recognition (OCR) has been used to transform this frequency translational image into words. The segmented words in the newspaper image are fed into the proposed DL architecture to obtain the classification results. These classification results have been used to find the Euclidean distances with respect to the databases in order to identify the content of the newspaper image.

Keywords

Newspaper, Images, Deep Learning, Spatial Image, Retrieval.

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