Francisco J. García-Ugalde

Robust hybrid color image watermarking method based on DFT domain and 2D histogram modification

In this paper, we present a robust hybrid watermarking method applied to color images for authentication, which presents robustness against several distortions. Due to the different nature of common signal processing and geometrical attacks, two different techniques for embed a same watermark are used in this method. In the first one, the luminance component (Y) information is used to embed the watermark bit sequence into the magnitude of the middle frequencies of the Discrete Fourier Transform (DFT). In the second one, a selected region of 2D histogram composed by blue-difference and red-difference (Cb–Cr) chrominance components is modified according to the watermark bit sequence. The quality of the watermarked image is measured using the following well-known indices peak signal to noise ratio (PSNR), visual information fidelity (VIF) and structural similarity index (SSIM). The difference color of the watermarked image is obtained using the normalized color difference (NCD) measure. The experimental results show that the proposed method provides robustness against several geometric distortions, signal processing operations, combined distortions and photo editing. The comparison with the previously reported methods based on different techniques is also provided.

Robust watermarking method in DFT domain for effective management of medical imaging

In general, management of medical data is achieved by several issues of medical information such as authentication, security, integrity, privacy, among others. Because medical images and their related electronic patient record (EPR) data are stored separately; the probability of corruption of this information or their detachment from the corresponding EPR data could be very high. Losing data from the corresponding medical image may lead to a wrong diagnostic. Digital watermarking has recently emerged as a suitable solution to solve some of the problems associated with the management of medical images. This paper proposes a robust watermarking method for medical images to avoid their detachment from the corresponding EPR data in which the watermark is embedded using the digital imaging and communications in medicine standard metadata together with cryptographic techniques. In order to provide a high robustness of the watermark while preserving at the same time a high quality of the watermarked images, the generated watermark is embedded into the magnitude of the middle frequencies of the discrete Fourier transform of the original medical image. During the detection process, the watermark data bits are recovered and detected using the bit correct rate criterion. Extensive experiments were carried out, and the performance of the proposed method is evaluated in terms of imperceptibility, payload, robustness and detachment detection. Quantitative evaluation of the watermarked images is performed by using three of the more common metrics: the peak signal-to-noise ratio, structural similarity index and visual information fidelity. Experimental results show the watermark robustness against several of the more aggressive geometric and signal processing distortions. The receiver operating characteristics curves also show the desirable detachment detection performance of the proposed method. A comparison with the previously reported methods with similar purposes respect to the proposed method is also provided.

An efficient color descriptor based on global and local color features for image retrieval

In the context of content-based image retrieval (CBIR) problem, an image is represented by feature vectors called descriptors, whose efficiency is essential to obtain a good performance in the image indexing and retrieval tasks. In this paper, we propose an algorithm to obtain an efficient color-based descriptor, which is a combination of Color Correlogram (CC) and Dominant Color (DC). The color-based descriptors, such as Histogram Intersection (HI) and DC take into account the global distribution of color in an image, while CC takes into account the local color distribution. So the combination of global and local color distribution provides a good image description. By its design, the proposed descriptor is more compact compared with the CC descriptor, which allows reducing computational complexity. Using the Average Retrieval precision (ARP) with different factors the effectiveness of the proposed descriptor is evaluated and compared with the conventional color-based descriptors, such as HI, CC and DC. The image database used in this work contains 500 images with 25 categories randomly selected from the Corel Dataset.

Robust digital image watermarking using interest points and DFT domain

In this paper we present a robust watermarking method, in which the watermark is embedded into the magnitude of the middle frequencies of the Discrete Fourier Transform (DFT). To allow the correct watermark detection, even if the image has been distorted, the Speeded Up Robust Feature (SURF) is used. During the embedding process the SURF points are estimated and stored in advance to be used during the detection process. In the detection process, the SURF points of the distorted image are estimated, which are used together with the stored ones to compute the affine-transformation parameters. Using these parameters the geometric distortion is corrected before applying the cross-correlation operation used for watermark detection. The quality of the watermarked image is measured using the Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index (SSIM). Experimental results show that the proposed method provides robustness against several geometric distortion and signal processing operations.

Segmentation algorithm for image sequences from a pel-recursive motion field

We present an algorithm to segment image sequences form motion information. A dense vector filed estimated by a Wiener-based pel-recursive method represents the key to separate a viewed scene into regions with different apparent displacement, according to a four-parameter motion model. A preprocessing stage using mathematical morphology enhances pel-recursive motion estimation. The proposed segmentation model, based on Markov Random Fields theory , considers-- besides the motion field--other information sources that help describe the problem more accurately. The maximum a posteriori criterion is used for the optimization of the solution, and performed with a deterministic approach. The complete segmentation algorithm includes initializing, region numbering and labeling, parameter estimation of the motion model in each region, and optimization of the segmentation field. Results on synthetic and real sequences are shown.

Content Based Video Retrival System for Mexican Culture Heritage Based on Object Matching and Local-Global Descriptors

Multimedia data and networking technologies have had a highly growing during the last decade, with these changes users have changed from text to content based video retrieval systems due to its better performance. We propose a fast content-based video retrieval system which involves the combination of a local descriptor obtained from the speeded-up robust feature algorithm together with an effective and fast object matching operation. To save computational time, compressed video data are partially decoded in order to get discrete cosine transform coefficients of key frames, which are used to obtain sub-block coefficients and a down-sampling version of frames. The preliminary results are ranking using an efficient color descriptor based on color correlogram and dominant color descriptors. To measure the performance of the proposed technique the precision and recall metrics are used. The experimental results show the accuracy of the proposed method applied to a database of Mexican Culture Heritage videos.

Performance of HSR and QPP-based interleavers for turbo coding on power line communication systems

In this paper, the performance of different type and length interleavers for turbo codes is analyzed in the context of power line communication systems. This system typically operates in very noisy environments; the noise, in this channel, is a combination of colored, narrow band and impulsive noises; it has also strong amplitude attenuations. The digital modulation frequently employed in power line communication to counteract the channel’s noise effects is the orthogonal frequency division multiplexing due to its high spectral efficiency and robustness in multipath fading environments; hence, it is also considered in our experimentation. We report the performance of turbo codes with the two types of interleavers: the high-spread random and the based quadratic permutation polynomial. The constituent codes are part of the 3GPP standard. Finally, it is used a punctured matrix in order to achieve a coding rate of 1/2. The performance is evaluated in terms of bit error rate, through the way of simulations.

Robust encoded spread spectrum image watermarking in contourlet domain

This paper presents a new robust watermarking system for digital images. The main challenge in every watermarking algorithm is to create a high capable, robust and imperceptible scheme. Unlike other watermarking methods, our system encodes the watermark using a convolutional encoder and embeds the encoded watermark in the transform domain of an image using a direct sequence spread spectrum technique to accomplish a high robustness. The embedded watermark bits are retrieved computing the correlation between the watermarked coefficients and the pseudorandom sequences used in the watermark embedding. In addition, the retrieved bits are decoded using the Viterbi algorithm to recover the hidden watermark. A low perceptibility of the watermark on the host image is preferred, therefore, some features of the human visual system are considered for achieving a high perceptual quality of the watermarked image. For assessing such quality, a structural similarity index measure is adopted. Our watermarking algorithm is robust to common image processes in the spatial domain.

Image analysis by basis pursuit

This paper presents an image analysis by basis pursuit, such analysis, depending the dictionary employed, can provide an image multi-scale edge representation such as the Mallat and Hwangs representation. When a stationary dictionary is employed while processing images by basis pursuit, the coefficients selected from the dictionary can characterize very well the most important image features, because of this well characterization we obtain directly an image edge representation from the coefficients selected. According to the results presented in this paper, we can say processing images by basis pursuit provides a new alternative to multi-scale image edge detection which should be exploited and expanded to other image processing applications such as image compression, de-noising, segmentation, image enhancement or image interpretation.

Image restoration, deblurring, and coding by means of polynomial transforms

We present a technique for image processing and coding based on the polynomial transform. This is an image representation model that analyzes an image by locally expanding it into a weighted sum of orthogonal polynomials. In this article we use the polynomial transform to build applications, astronomical images being the main target. The applications that we propose are developed on pyramidal structures. Their purpose is to analyze an astronomial image at different spatial scales, generating applications such as coding based on deblurring from its representation at a lower scale and followed by a scheme of prediction; another application is the reduction of noise in images generated by an astronomical acquisition system.