Rank-based image watermarking method with high embedding capacity and robustness

This paper presents a novel rank-based method for image watermarking. In the watermark embedding process, the host image is divided into blocks, followed by the 2-D discrete cosine transform (DCT). For each image block, a secret key is employed to randomly select a set of DCT coefficients suitable for watermark embedding. Watermark bits are inserted into an image block by modifying the set of DCT coefficients using a rank-based embedding rule. In the watermark detection process, the corresponding detection matrices are formed from the received image using the secret key. Afterward, the watermark bits are extracted by checking the ranks of the detection matrices. Since the proposed watermarking method only uses two DCT coefficients to hide one watermark bit, it can achieve very high embedding capacity. Moreover, our method is free of host signal interference. This desired feature and the usage of an error buffer in watermark embedding result in high robustness against attacks. Theoretical analysis and experimental results demonstrate the effectiveness of the proposed method

The multimedia blockchain: a distributed and tamper-proof media transaction framework

A distributed and tamper proof media transaction framework is proposed based on the blockchain model. Current multimedia distribution does not preserve self-retrievable information of transaction trails or content modification histories. For example, digital copies of valuable artworks, creative media and entertainment contents are distributed for various purposes including exhibitions, gallery collections or in media production workflow. Original media is often edited for creative content preparation or tampered with to fabricate false propaganda over social media. However there is no existing trusted mechanism that can easily retrieve either the transaction trails or the modification histories. We propose a novel watermarking based Multimedia Blockchain framework that can address such issues. The unique watermark information contains two pieces of information: a) a cryptographic hash that contains transaction histories (blockchain transactions log) and b) an image hash that preserves retrievable original media content. Once the watermark is extracted, first part of the watermark is passed to a distributed ledger to retrieve the historical transaction trail and the latter part is used to identify the edited / tampered regions. The paper outlines the requirements, the challenges and demonstrates the proof of this concept

Color Image Analysis by Quaternion-Type Moments

International audienceIn this paper, by using the quaternion algebra, the conventional complex-type moments (CTMs) for gray-scale images are generalized to color images as quaternion-type moments (QTMs) in a holistic manner. We first provide a general formula of QTMs from which we derive a set of quaternion-valued QTM invariants (QTMIs) to image rotation, scale and translation transformations by eliminating the influence of transformation parameters. An efficient computation algorithm is also proposed so as to reduce computational complexity. The performance of the proposed QTMs and QTMIs are evaluated considering several application frameworks ranging from color image reconstruction, face recognition to image registration. We show they achieve better performance than CTMs and CTM invariants (CTMIs). We also discuss the choice of the unit pure quaternion influence with the help of experiments. appears to be an optimal choice

Analysis of the image moments sensitivity for the application in pattern recognition problems

Momenti slike su numerički deskriptori koji sadrže informaciju o svojstvima invarijantnim na translaciju, rotaciju, promjenu skale i neke oblike distorzije, a njihova analiza je jedna od metoda koje se često koriste pri analizi slika i raspoznavanju uzoraka. U okviru ove radnje razvijeni su algoritmi za računanje geometrijskih, Legendreovih, Zernikeovih, Fourier – Mellinovih te tri tipa Fourier – Jacobijevih momenata, kao i iz njih definiranih invarijanti slike u programskom jeziku MatLab uz rješavanje inverznog problema rekonstrukcije početnog ulaza. Za sve tipove momenata osim najjednostavnijih geometrijskih definirani su vektori osjetljivosti na rotaciju i promjenu skale čije su komponente oni članovi skupa koji nose značajnije informacije o ulaznoj slici. Primjenom novih deskriptora na klasifikaciju rukom pisanih slova i identifikacijskih fotografija osoba pokazano je da je relevantna informacija o ulazu na taj način sačuvana, a njihov je izračun znatno brži i jednostavniji uz zadržanu sposobnost jednoznačnog raspoznavanja uzoraka. Korištenjem momenata slike i vektora osjetljivosti analizirani su znakovi s dvaju glagoljskih spomenika te utvrđeno postojanje mješavine znakova trokutastog i okruglog modela glagoljice. Metoda je primijenjena i na klasifikaciju tragova puzanja ličinki mutanata vinske mušice za potrebe proučavanja odgovora živčanog sustava na različite podražaje.Image moments are numerical descriptors invariant to translation, rotation, change of scale and some types of image distortion and their analysis is one of the most often used methods in image processing and pattern recognition. In this work, algorithms for calculation of geometric, Legendre, Zernike, Fourier – Mellin and three types of Fourier – Jacobi moments were implemented in MatLab. Hu's, affine and blur invariants were also obtained as well as inverse problem of input image reconstruction solved. For each type of image moments exept geometric ones the set of sensitivity vectors for rotation and scale were defined. Their components are those image moments which describe more important features of the input image. These new descriptors were applied for classification of handwritten letters and identifying personal photos. It was shown that the process of such descriptor calculation is much faster and simpler while preserving all the relevant information about input image. Using this method, the signs carved in two glagolitic inscriptions were analyzed and the mixture of triangular and round glagolitic letters found. The method was also applied to classification of the mutant fruit fly larvae crawling trails which is needed in studying responses of the nervous system to different stimuli

Analysis of the image moments sensitivity for the application in pattern recognition problems

Momenti slike su numerički deskriptori koji sadrže informaciju o svojstvima invarijantnim na translaciju, rotaciju, promjenu skale i neke oblike distorzije, a njihova analiza je jedna od metoda koje se često koriste pri analizi slika i raspoznavanju uzoraka. U okviru ove radnje razvijeni su algoritmi za računanje geometrijskih, Legendreovih, Zernikeovih, Fourier – Mellinovih te tri tipa Fourier – Jacobijevih momenata, kao i iz njih definiranih invarijanti slike u programskom jeziku MatLab uz rješavanje inverznog problema rekonstrukcije početnog ulaza. Za sve tipove momenata osim najjednostavnijih geometrijskih definirani su vektori osjetljivosti na rotaciju i promjenu skale čije su komponente oni članovi skupa koji nose značajnije informacije o ulaznoj slici. Primjenom novih deskriptora na klasifikaciju rukom pisanih slova i identifikacijskih fotografija osoba pokazano je da je relevantna informacija o ulazu na taj način sačuvana, a njihov je izračun znatno brži i jednostavniji uz zadržanu sposobnost jednoznačnog raspoznavanja uzoraka. Korištenjem momenata slike i vektora osjetljivosti analizirani su znakovi s dvaju glagoljskih spomenika te utvrđeno postojanje mješavine znakova trokutastog i okruglog modela glagoljice. Metoda je primijenjena i na klasifikaciju tragova puzanja ličinki mutanata vinske mušice za potrebe proučavanja odgovora živčanog sustava na različite podražaje.Image moments are numerical descriptors invariant to translation, rotation, change of scale and some types of image distortion and their analysis is one of the most often used methods in image processing and pattern recognition. In this work, algorithms for calculation of geometric, Legendre, Zernike, Fourier – Mellin and three types of Fourier – Jacobi moments were implemented in MatLab. Hu's, affine and blur invariants were also obtained as well as inverse problem of input image reconstruction solved. For each type of image moments exept geometric ones the set of sensitivity vectors for rotation and scale were defined. Their components are those image moments which describe more important features of the input image. These new descriptors were applied for classification of handwritten letters and identifying personal photos. It was shown that the process of such descriptor calculation is much faster and simpler while preserving all the relevant information about input image. Using this method, the signs carved in two glagolitic inscriptions were analyzed and the mixture of triangular and round glagolitic letters found. The method was also applied to classification of the mutant fruit fly larvae crawling trails which is needed in studying responses of the nervous system to different stimuli

Robust and efficient Fourier-Mellin transform approximations for invariant grey-level image description and reconstruction

International audienceThis paper addresses the gray-level image representation ability of the Fourier-Mellin Transform (FMT) for pattern recognition, reconstruction and image database retrieval. The main practical di±culty of the FMT lies in the accuracy and e±ciency of its numerical approximation and we propose three estimations of its analytical extension. Comparison of these approximations is performed from discrete and ¯nite-extent sets of Fourier- Mellin harmonics by means of experiments in: (i) image reconstruction via both visual inspection and the computation of a reconstruction error; and (ii) pattern recognition and discrimination by using a complete and convergent set of features invariant under planar similarities. Experimental results on real gray-level images show that it is possible to recover an image to within a speci¯ed degree of accuracy and to classify objects reliably even when a large set of descriptors is used. Finally, an example will be given, illustrating both theoretical and numerical results in the context of content-based image retrieval

Digital Filters and Signal Processing

Digital filters, together with signal processing, are being employed in the new technologies and information systems, and are implemented in different areas and applications. Digital filters and signal processing are used with no costs and they can be adapted to different cases with great flexibility and reliability. This book presents advanced developments in digital filters and signal process methods covering different cases studies. They present the main essence of the subject, with the principal approaches to the most recent mathematical models that are being employed worldwide