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20172022
most citedDCT-domain Deep Convolutional Neural Networks for Multiple JPEG Compression Classification

53 citations · 180 across the 13 of their papers we have counts for

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5 papers · 1 filter

cs.MM2018★ 9 cited

First Steps Toward CNN based Source Classification of Document Images Shared Over Messaging App

Sharad Joshi, Suraj Saxena, Nitin Khanna

Knowledge of source smartphone corresponding to a document image can be helpful in a variety of applications including copyright infringement, ownership attribution, leak identific…

cs.MM2018★ 23 cited

Source Printer Classification using Printer Specific Local Texture Descriptor

Sharad Joshi, Nitin Khanna

The knowledge of source printer can help in printed text document authentication, copyright ownership, and provide important clues about the author of a fraudulent document along w…

cs.MM2017★ 53 cited

DCT-domain Deep Convolutional Neural Networks for Multiple JPEG Compression Classification

Vinay Verma, Nikita Agarwal, Nitin Khanna

With the rapid advancements in digital imaging systems and networking, low-cost hand-held image capture devices equipped with network connectivity are becoming ubiquitous. This eas…

cs.MM2017★ 49 cited

Single Classifier-based Passive System for Source Printer Classification using Local Texture Features

Sharad Joshi, Nitin Khanna

An important aspect of examining printed documents for potential forgeries and copyright infringement is the identification of source printer as it can be helpful for ascertaining…

cs.MM2017★ 3 cited

Passive Classification of Source Printer using Text-line-level Geometric Distortion Signatures from Scanned Images of Printed Documents

Hardik Jain, Gaurav Gupta, Sharad Joshi +1

In this digital era, one thing that still holds the convention is a printed archive. Printed documents find their use in many critical domains such as contract papers, legal tender…