scholarly journals Copy Move Image Forgery Detection with Exact Match Block Based Technique

2019 ◽  
Vol 12 (Issue 3) ◽  
pp. 123-131
Author(s):  
Priyanka Arora ◽  
Derminder Singh
Keyword(s):  
Execution Time ◽  
Digital Images ◽  
Block Size ◽  
Forgery Detection ◽  
Exact Match ◽  
Image Forgery ◽  
File Formats ◽  
The Common ◽  
Block Based ◽  
Block Sizes

Digital images are a momentous part of today’s digital communication. It is very easy to manipulate digital images for hiding some useful information by image rendering tools such as Adobe Photoshop, Microsoft Paint etc. The common image forgery which is easy to carry out is copy-move in which some part of an image is copied and pasted on another part of the same image to hide the important information. In this paper we propose an algorithm to spot the copy-move forgery based on exact match block based technique. The algorithm works by matching the regions in image that are equivalent by matching the small blocks of size b b. The program is tested for 45 images of mixed image file formats by considering block sizes 2, 4, 6, 8, 10, 12, 14, and 16. It is observed from the experimental results that the proposed algorithm can detect copy-move image forgery in TIF, BMP and PNG image formats only. Results reveal that as the block size increases, execution time (time taken by CPU to display output) also increases but the number of detected forged images increases till block size 10 and attains saturation thereafter. Consequently block size should be set to 10 for getting good results in terms of less execution time.

Comparative Study of Various Forgery Detection Approach for Image Processing

2021 ◽  
Vol 10 (1) ◽  
pp. 18-26
Author(s):  
Manish KUMARI ◽  
Rajesh SHARMA
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Comparative Study ◽  
Digital Images ◽  
Real Life ◽  
Forgery Detection ◽  
Image Forgery ◽  
Detection Approach

Considering the availability of powerful image analysis and editing tools, digital images are easy to change and transfer. This is necessary to link or erase any important elements from any image without escaping any valid visible signs of interfering. Including its real-life apps in different areas, the copy move forgery method is analyzed in depth. Implementation phases for the detection of image forgery are also clarified, accompanied by various approaches using copy move forgery approach.

Block-Based High Capacity Multilevel Image Steganography

2016 ◽  
Vol 25 (08) ◽  
pp. 1650091 ◽  
Author(s):  
Geeta Kasana ◽  
Kulbir Singh ◽  
Satvinder Singh Bhatia
Keyword(s):  
Digital Images ◽  
High Capacity ◽  
Block Size ◽  
Visual Quality ◽  
Cover Image ◽  
Embedding Capacity ◽  
Secret Data ◽  
Block Based ◽  
High Embedding Capacity

This paper proposes a block-based high capacity steganography technique for digital images. The cover image is decomposed into blocks of equal size and the largest pixel of each block is found to embed the secret data bits and also the smallest pixel of each block is used for embedding to enhance the capacity. Embedding of secret data is performed using the concept that the pixel of a cover image has only two states — even and odd. Multilevel approach is also combined in the proposed technique to achieve high embedding capacity. In order to make the proposed technique more secure, a key is generated using embedding levels, block size, pixel embedding way, encryption parameters, and starting blocks of each embedding levels. Embedding capacity and visual quality of stego images generated by the proposed steganography technique are higher than the existing techniques. Steganalysis tests have been performed to show the un-detectability and imperceptibility of the proposed technique.

scholarly journals An Improved Discrete Cosine Transformation Block Based Scheme for Copy-move Image Forgery Detection

2019 ◽  
Vol 9 (2) ◽  
Author(s):  
Abdulraheem Hassanat Oyiza ◽  
Mohd Aizaini Maarof
Keyword(s):  
Detection Algorithm ◽  
Detection Accuracy ◽  
Forgery Detection ◽  
Image Block ◽  
Discrete Cosine Transformation ◽  
Image Forgery ◽  
Robust Detection ◽  
Image Forgery Detection ◽  
Dct Coefficients ◽  
Block Based

Copy-moved forgery is a common method to manipulate images. Several attempts of image forgery have been discovered and involves a region been duplicated and copied and pasted on another region of the same image in other to achieve selfish gain. Generally, there are two classification of copy-move forgery detection technique such as the block-based and key point-based. The block-based division is mostly used and divides image into blocks during the stage of image pre-processing before features are extracted, whereas key-point based technique skips the division of image into blocks and directly extracts different local feature from the image. In this paper, we review various block based and key point approach which has been proposed by various researchers. There is a problem of achieving a balance between improving the detection accuracy and having minimal computational complexity. The proposed technique is based on an improved DCT based copy-move image forgery detection (IDB-CFD), which involves using an octagonal block to reduce the number of features for matching, thereby improving detection accuracy while having minimal complexity. The analysis of this work as compared to previous proposed works which is based on a robust detection algorithm for copy-move image forgery (RDA-CF) and involves using circle block to reduce the number of features, results show that previous work represents about 79% of the quantized DCT coefficients on each image block and this proposed work represents about 85% of quantized DCT coefficients, therefore, recovery of about 6% more features using the IDB-CFD technique was observed as the improvement over the previously proposed RDA-CF.

scholarly journals Copy-Move Forgery Detection in Digital Images using Neural Network

2020 ◽  
Vol 9 (4) ◽  
pp. 1560-1564
Keyword(s):  
Neural Network ◽  
Digital Images ◽  
Experimental Results ◽  
Image Editing ◽  
Forgery Detection ◽  
Software Applications ◽  
Key Points ◽  
Block Based ◽  
Copy Move Forgery Detection ◽  
Multiple Stages

Due to easy availability of image editing software applications, many of the digital images are tempered, either to hide some important facts of the image or just to enhance the image. Hence, the integrity of the image is compromised. Thus, in order to preserve the authenticity of an image, it is necessary to develop some algorithms to detect counterfeit parts of an image, if there is any. Two kinds of classic methods exist for the detection of forgery: the key- point based method in which major key points of the image is found and forged part is detected and the block based method that locates the forged part by sectioning the whole image into blocks. Unlike these two classic methods that require multiple stages, our proposed CNN solution provides better image forgery detection. Our experimental results revealed a better forgery detection performance than any other classic approaches.

scholarly journals Image Splicing-Based Forgery Detection Using Discrete Wavelet Transform and Edge Weighted Local Binary Patterns

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Muhammad Hameed Siddiqi ◽  
Khurshed Asghar ◽  
Umar Draz ◽  
Amjad Ali ◽  
Madallah Alruwaili ◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Digital Image ◽  
Digital Images ◽  
Local Binary Patterns ◽  
Discrete Wavelet ◽  
Forgery Detection ◽  
Image Splicing ◽  
Image Forgery ◽  
Image Forgery Detection

With the advancement of the multimedia technology, the extensive accessibility of image editing applications makes it easier to tamper the contents of digital images. Furthermore, the distribution of digital images over the open channel using information and communication technology (ICT) makes it more vulnerable to forgery. The vulnerabilities in telecommunication infrastructure open the doors for intruders to introduce deceiving changes in image data, which is hard to detect. The forged images can create severe social and legal troubles if altered with malicious purpose. Image forgery detection necessitates the development of sophisticated techniques that can efficiently detect the alterations in the digital image. Splicing forgery is commonly used to conceal the reality in images. Splicing introduces high contrast in the corners, smooth regions, and edges. We proposed a novel image forgery detection technique based on image splicing using Discrete Wavelet Transform and histograms of discriminative robust local binary patterns. First, a given color image is transformed in YCbCr color space and then Discrete Wavelet Transform (DWT) is applied on Cb and Cr components of the digital image. Texture variation in each subband of DWT is described using the dominant rotated local binary patterns (DRLBP). The DRLBP from each subband are concatenated to produce the final feature vector. Finally, a support vector machine is used to develop image forgery detection model. The performance and generalization of the proposed technique were evaluated on publicly available benchmark datasets. The proposed technique outperformed the state-of-the-art forgery detection techniques with 98.95% detection accuracy.

scholarly journals Key Point and Block based Feature Matching for Effective Image Forgery Detection

IJARCCE ◽  
2017 ◽  
Vol 6 (3) ◽  
pp. 714-717
Author(s):  
Durga Jetthy ◽  
Purva Gubbawar ◽  
Aditya Kumar Gupta ◽  
Mrs. Panwar S.A.
Keyword(s):  
Feature Matching ◽  
Forgery Detection ◽  
Image Forgery ◽  
Image Forgery Detection ◽  
Block Based

A survey on block based copy move image forgery detection techniques

2015 ◽  
Author(s):  
Toqeer Mahmood ◽  
Tabassam Nawaz ◽  
Rehan Ashraf ◽  
Mohsin Shah ◽  
Zakir Khan ◽  
...  
Keyword(s):  
Forgery Detection ◽  
Image Forgery ◽  
Detection Techniques ◽  
Image Forgery Detection ◽  
Block Based
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