Robust Image Hashing Technique for Content Authentication based on DWT

Vadlamudi, Lokanadham Naidu; Vaddella, Rama Prasad V.; Vasumathi, D.

doi:10.1007/978-981-10-2104-6_17

Cited by 2 publications

(4 citation statements)

References 11 publications

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“…2-Level DWT is generated from L*a*b of input image. Sequence of circles on approximation and feature is applied LL2 band for hash generation [12]. Invariance property of the Fourier Mellin Transform (FMT) is captured to generate hash [13].…”

Section: Review Of Literaturementioning

confidence: 99%

“…To achieve this, like our pervious proposed approaches, histogram is not compressed and double bit quantization (DBQ) is preferred over single bit quantization (SBQ) to produce quality hash code. Following equation (11) and (12) represent equation for double bit quantization.…”

Section: Weighted Cslbpmentioning

confidence: 99%

“…Quantized Threshold round Original value /  min hb (12) Quantized Threshold represents threshold. It quantized histogram values into three levels 0, 1 and 2.…”

Section:    mentioning

confidence: 99%

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Image Hashing Using DWT-CSLBP

Patil¹,

Sarode²

2019

JCP

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Center Symmetric Local Binary Pattern (CSLBP) is widely used in texture and object detection, but its utilization in image hashing is still limited. Image hashing is a powerful technique to identify whether image content is changed or preserved. Two main issues in image hashing are its compact length and its robust discrimination power. To deal with these issues, a robust image hashing method is proposed by combining features of CSLBP and Discrete Wavelet Transform(DWT). CSLBP is applied on LL band of DWT for compact length hash. Discrimination power of hashing is enhanced by weigh factor which comprises information from all sub bands of 1-Level DWT. All sub-band images of 1-Level DWT is combined to form secondary image. Local statistical features like Standard Deviation and Magnitude Average are calculated to obtain local weight factor MASD (Magnitude Average and Standard Deviation). Weighted LL-CSLBP histogram is constructed using this weight factor. Experimental results are demonstrated with Receiver Operating Characteristics (ROC) and Normalized Hamming Distance (NHD). The results shows that, the proposed scheme is robust against content preserving operations and sensitive to malicious operations.

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Section: Review Of Literaturementioning

confidence: 99%

Section: Weighted Cslbpmentioning

confidence: 99%

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Image Hashing Using DWT-CSLBP

Patil¹,

Sarode²

2019

JCP

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“…Sub band images are generated by applying 2-level DWT on the input color image. LL2 sub-band image arranged in concentric rings to extract features for hash creation [17]. Features such as Discrete Cosine Transformation (DCT) and Gray Level Co-occurrence Matrix (GLCM) are extracted in circular rings to generate rotation invariant hash [18].…”

Section: Introductionmentioning

confidence: 99%

Adaptive CSLBP compressed image hashing

Patil¹,

Sarode²

2019

IJECE

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Hashing is popular technique of image authentication to identify malicious attacks and it also allows appearance changes in an image in controlled way. Image hashing is quality summarization of images. Quality summarization implies extraction and representation of powerful low level features in compact form. Proposed adaptive CSLBP compressed hashing method uses modified CSLBP (Center Symmetric Local Binary Pattern) as a basic method for texture extraction and color weight factor derived from L*a*b* color space. Image hash is generated from image texture. Color weight factors are used adaptively in average and difference forms to enhance discrimination capability of hash. For smooth region, averaging of colours used while for non-smooth region, color differencing is used. Adaptive CSLBP histogram is a compressed form of CSLBP and its quality is improved by adaptive color weight factor. Experimental results are demonstrated with two benchmarks, normalized hamming distance and ROC characteristics. Proposed method successfully differentiate between content change and content persevering modifications for color images.

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Robust Image Hashing Technique for Content Authentication based on DWT

Cited by 2 publications

References 11 publications

Image Hashing Using DWT-CSLBP

Image Hashing Using DWT-CSLBP

Adaptive CSLBP compressed image hashing

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