Due to the availability of various image processing tools forgery over an image can be performed very easily but very difficult to identify. In copy-move forgery, a segment is copied from the original image and pasted at some other location on the same image to hide significant objects of image or to bring additional information which is originally not present in image. Nowadays, this forgery technique is drawing researcher's attention. Till now many solutions are presented by researchers to detect such type of forgery in images. Several post-processing operations like rotation, alteration in intensity, noise addition, filtering and blurring can be applied over copy-moved segment which makes detection of forgery very difficult. Copy-move forgery detection is mainly based on finding similarity present in an image and establish a relationship between genuine image parts and pasted portion of the image. This paper is centralized towards providing survey to forgery detection techniques based on different block-based methods. In block-based methods image is divided in blocks of fixed dimension and further features are extracted corresponding to each block of image. Forged blocks are identified utilizing the similarity present between feature vectors.

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Correcting Multi-focus Images via Simple Standard Deviation for Image Fusion

Firas A. Jassim

Статья научная

Image fusion is one of the recent trends in image registration which is an essential field of image processing. The basic principle of this paper is to fuse multi-focus images using simple statistical standard deviation. Firstly, the simple standard deviation for the kk window inside each of the multi-focus images was computed. The contribution in this paper came from the idea that the focused part inside an image had high details rather than the unfocused part. Hence, the dispersion between pixels inside the focused part is higher than the dispersion inside the unfocused part. Secondly, a simple comparison between the standard deviation for each kk window in the multi-focus images could be computed. The highest standard deviation between all the computed standard deviations for the multi-focus images could be treated as the optimal that is to be placed in the fused image. The experimental visual results show that the proposed method produces very satisfactory results in spite of its simplicity.

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Cosine Modulated Non-Uniform Filter Bank with Improved Computational Efficiency

Jyotsna v. Ogale, Alok Jain

Статья научная

In this correspondence, a simple design method for multirate near perfect reconstruction (NPR) integer decimated filter bank with non-uniform frequency spacing and linear phase property, that involves optimization of only single parameter, is proposed. It is derived from the uniform cosine modulated filter bank (CMFB) by merging some relevant band pass filters. The design procedure and the structure of the uniform CMFB are mostly preserved in the non-uniform implementation. The parent filter of the filter bank is formulated as an interpolated finite impulse response (IFIR) filter. The IFIR digital filters permit efficient hardware implementations due to less number of multiplier coefficients. Design examples show that the proposed approach provides good performance with less computational complexity at the cost of slight increase in system delay.

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