Detection of Copy-Move Forgery Exploiting LBP Features with Discrete Wavelet Transform

Abstract

Copy-move forgery is being used at various fields to hide significant information or to append additional information in image. Image forgery results in false interpretations. In this forgery, one section of image is copied and then it is pasted over the same image at different location. Although, various techniques are suggested by researchers but finding forged section of varying size and located at different locations on image is complicated. To resolve such problems we introduce a new hybrid approach for finding copy-move forgery based on Discrete Wavelet Transform with Local Binary Pattern. At First, image is moldered into three color components. Discrete Wavelet Transform is applied over the image which results in four sub bands. Approximation sub image contains low frequency components having maximum information. LL subimage is divided in overlapping blocks. Local Binary Pattern is calculated for blocks to generate descriptors to match similar blocks. Shift vectors are computed to find group of block pairs with similar shifting. It is observed by our experimental results that proposed method can efficiently detect manipulated images having different forgery size with high detection accuracy and low false positive rate as comparison to other state-of-the-art.

Review on Local Binary Patterns Variants as Texture Descriptors for Copy-Move Forgery Detection

“…Dixit et al [29] introduced a new hybrid approach based on Discrete Wavelet Transform with LBP to resolve problems of finding a forged section of varying size and located at different locations on the image. The proposed method gave a high accuracy for plain copy-move forgery detection and low complexity of block pairs matching as lexicographical sorting had been used.…”

Tampering Detection and Localization in Images from Social Networks: A CBIR Approach

“…These methods, also called Local Descriptor-based forgery detection techniques, are typically based on feature matching. Block-based approaches split the image into overlapping blocks and extract features, such as DCT, DWT, histogram of co-occurrences on the image residual [11], Zernike moments, or Local Binary Pattern (LBP) [9]. Keypoints-based approaches compute features, usually SIFT or SURF [1,10], on local regions characterized by a high entropy.…”

Comércio intra-industrial brasileiro: análise dos determinantes através da equação gravitacional

“…Por essa razão, os modelos pioneiros de CII excluem de suas formulações as idéias das teorias tradicionais, introduzindo a competição monopolística, retornos crescentes à escala, combinados com preferências homogêneas de consumo pelos parceiros comerciais, para explicar a existência e o significado do CII. Esses modelos são chamados de neo-Chamberlianos (DIXIT;STIGLITZ, 1977;KRUGMAN, 1979KRUGMAN, , 1980KRUGMAN, , 1982, ou identificados como modelos neo-Hotelling (LANCASTER 1979(LANCASTER , 1980. Helpman e Krugman (1985) apresentam um modelo que busca integrar essas teorias, denominado modelo Chamberlin -Heckscher -Ohlin -Samuelson (CHOS).…”

“…Modelos teóricos foram desenvolvidos para explicar o CII (DIXIT;STIGLITZ, 1977;LANCASTER, 1979;KRUGMAN, 1979), sendo que a maioria se pauta em um contexto analítico envolvendo mercados que operam segundo uma estrutura de competição monopolística e fatores como diferenças nos gostos e preferências dos consumidores; possibilidade de explorar economias de escala e diferenciação de produto são relevantes para justificar a ocorrência do comércio. Os modelos empíricos desenvolvidos a partir dessas teorias apontam características relacionadas com os países, como a renda per capita e a diferença entre as rendas dos países, e relacionadas à indústria, tais como barreiras comerciais, diferenciação do produto e investimento direto do exterior.…”