HSB-SPAM: An Efficient Image Filtering Detection Technique

Saurabh Agarwal,Ki-Hyun Jung

doi:10.3390/app11093749

Abstract

Median filtering is being used extensively for image enhancement and anti-forensics. It is also being used to disguise the traces of image processing operations such as JPEG compression and image resampling when utilized in image de-noising and smoothing tool. In this paper, a robust image forensic technique namely HSB-SPAM is proposed to assist in median filtering detection. The proposed technique considers the higher significant bit-plane (HSB) of the image to highlight the statistical changes efficiently. Further, multiple difference arrays along with the first order pixel difference is used to separate the pixel difference, and Laplacian pixel difference is applied to extract a robust feature set. To compact the size of feature vectors, the operation of thresholding on the difference arrays is also utilized. As a result, the proposed detector is able to detect median, mean and Gaussian filtering operations with higher accuracy than the existing detectors. In the experimental results, the performance of the proposed detector is validated on the small size and post JPEG compressed images, where it is shown that the proposed method outperforms the state of art detectors in the most of the cases.

Highlights

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The UCIDv2.0 [36] database (UCID) has been selected to evaluate the performance of the proposed method since the UCIDv2.0 [36] database (UCID) database has been one of the prime databases being used in literature
The images of size 256 × 256, 128 × 128, 64 × 64, and 32 × 32 pixels are considered for experimental purposes by cropping center part of original images of UCID database images as shown in Figure 7b, which can eliminate the padding artifacts

Summary

Introduction

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Methods

Results

Conclusion