Imran Usman

Technical Communication: Authentication and recovery of images using multiple watermarks

A novel wavelet domain based semi-fragile watermarking scheme is presented for securing digital content and to concisely determine the regions where the integrity fails. In addition, another watermark is embedded to perform self-recovery in case of malicious attack. The security weaknesses of the traditional block-based approaches are circumvented by correlating the watermark bits with wavelet coefficients of the approximation subband of the host image. Semi-fragility exhibits robustness to JPEG compression, while recovery attribute makes the scheme suitable for video surveillance and remote sensing applications. Experimental investigations are performed to evaluate the performance of the proposed multiple semi-fragile watermarks and shows the suitability of the proposed approach for accurate authentication and recovery based applications.

BCH coding and intelligent watermark embedding: Employing both frequency and strength selection

This paper presents a novel approach of adaptive visual tuning of a watermark in Discrete Cosine Transform (DCT) domain. The proposed approach intelligently selects appropriate frequency bands as well as optimal strength of alteration. Genetic Programming (GP) is applied to structure the watermark by exploiting both the characteristics of human visual system and information pertaining to a cascade of conceivable attacks. The developed visual tuning expressions are dependent on frequency and luminance sensitivities, and contrast masking. To further enhance robustness, spread spectrum based watermarking and Bose-Chadhuri-Hocquenghem (BCH) coding is employed. The combination of spread spectrum sequence, BCH coding and GP based non-linear structuring makes it extremely difficult for an attacker to gain information about the secret knowledge of the watermarking system. Experimental results show the superiority of the proposed approach against the existing approaches. Especially, the margin of improvement in robustness will be of high importance in medical and context aware related applications of watermarking.

Intelligent reversible watermarking and authentication: Hiding depth map information for 3D cameras

In this paper, we propose an application for 3D cameras by reversibly hiding the depth map in the corresponding 2D images. The proposed technique is prospective in cameras capable of capturing simultaneously the 2D image and resultant depth map of an object. 3D cameras equipped with self-embedding capability can serve two additional purposes, protection of the captured image and secure transmission of its depth map. The reversible watermarking, in addition to other features, guarantees the lossless recovery of an original image and separation of its depth map when required. For this purpose, a reversible watermarking scheme, based on genetic algorithm (GA), has been proposed which computes suitable threshold for each block of coefficients in the wavelet domain. Thus, a tradeoff is made between watermark imperceptibility and capacity using GA. The threshold map is embedded in addition to the actual payload and thus the proposed approach does not require histogram pre-processing in order to avoid overflow/underflow. The same threshold map has been used for authentication purpose by correlating it with the low-frequency coefficients of the 2D transformed image. Further to exploit the inherent redundancy in the depth map, which is the actual payload in this case, lossless compression has been employed before its embedding. Similarly, besides secret key-based permutation, a cryptographic layer is overlaid on the watermarking layer for security purposes. Experiments conducted on images and depth maps, obtained using a 3D camera and an optical microscopic system, validate the proposed concept.

Iris localization in frontal eye images for less constrained iris recognition systems

Commercial iris recognition systems do not perform well for non-ideal data, because their iris localization algorithms are specifically developed for controlled data. This paper presents a robust iris localization algorithm for less constrained data. It includes: (i) suppressing specular reflections; (ii) localizing the iris inner (pupil circle) and outer (iris circle) boundaries in a two-phase strategy. In the first phase, we use Hough transform, gray level statistics, adaptive thresholding, and a geometrical transform to extract the pupil circle in a sub-image containing a coarse pupil region. After that, we localize iris circle in a sub-image centered at the pupil circle. However, if the first phase fails, the second phase starts, where first we localize a coarse iris region in the eye image. Next, we extract pupil circle within the coarse iris region by reusing procedure of first phase. Following that, we localize iris circle. In either of the two phases, we validate the pupil location by using an effective occlusion transform; and (iii) regularizing the iris circular boundaries by using radial gradients and the active contours. Experimental results show that the proposed technique is tolerant to off-axis eye images, specular reflections, non-uniform illumination; glasses, contact lens, hair, eyelashes, and eyelids occlusions.

Reliable iris localization using Hough transform, histogram-bisection, and eccentricity

The iris technology recognizes individuals from their iris texture with great precision. However, it does not perform well for the non-ideal data, where the eye image may contain non-ideal issues such as the off-axis eye image, blurring, non-uniform illumination, hair, glasses, etc. It is because of their iris localization algorithms, which are developed for the ideal data. In this paper, we propose a reliable iris localization algorithm. It includes localizing a coarse iris location in the eye image using the Hough transform and image statistics; localizing the pupillary boundary using a bi-valued adaptive threshold and the two-dimensional (2D) shape properties; localizing the limbic boundary by reusing the Hough accumulator and image statistics; and finally, regularizing these boundaries using a technique based on the Fourier series and radial gradients. The proposed technique is tested on the public iris databases: CASIA V1, CASIA-IrisV3-Lamp, CASIA-IrisV4-Thousand, IITD V1.0, MMU V1.0, and MMU (new) V2.0. Experimental results obtained on these databases show superiority of the proposed technique over some state of the art iris localization techniques.

A dynamic non-circular iris localization technique for non-ideal data

Display Omitted Robust iris inner contour localization within a sliding window.A fast and reliable technique for the iris outer contour localization.Iris contours regularization.Tolerance to rotated-iris images, specular reflections, hair, eyelids, and glasses.Applicable in real-time applications. Iris localization plays a decisive role in the overall iris biometric systems performance, because it isolates the valid part of iris. This study proposes a reliable iris localization technique. It includes the following. First, it extracts the iris inner contour within a sliding-window in an eye image using a multi-valued adaptive threshold and the two-dimensional (2D) properties of binary objects. Then, it localizes the iris outer contour using an edge-detecting operator in a sub image centered at the pupil center. Finally, it regularizes the iris contours to compensate for their non-circular structure. The proposed technique is tested on the following public iris databases: CASA V1.0, CASIA-Iris-Lamp, IITD V1.0, and the MMU V1.0. The experimental and accuracy results of the proposed scheme compared with other state-of-the-art techniques endorse its satisfactory performance.

Hiding depth map of an object in its 2D image: Reversible watermarking for 3D cameras

3D cameras are capable of capturing image and depth map of an object simultaneously. We propose a method to hide depth map, as a watermark, in its corresponding 2D image. 3D cameras enabled with this functionality could serve two purposes; protection of the captured image and secure transmission of its depth map.

Lossless Data Hiding Using Optimized Interpolation Error Expansion

Reversible data hiding technique enables the exact recovery of original contents upon extraction of embedding data. Many conventional watermarking algorithms that have been proposed so far, suffer from the problem of low embedding capacity. In many applications huge amount of data is required to embed and exact recovery of host image is also needed. Luos additive interpolation-error expansion technique [1] is a high capacity reversible method for data embedding without zero loss of host information. In this paper, we focus on improving payload and imperceptibility, and we propose an algorithm which is an extension of interpolation-error scheme using Particle Swarm Optimization (PSO) which better exploits estimation of missing pixel. The experimental results demonstrate that due to slight modification in interpolation-error technique, we achieve large hiding capacity and improved image quality compared with other schemes.

Authentication and recovery of digital images: Potential application in video surveillance and remote sensing

This paper presents a semi-fragile watermarking technique capable of both authenticating and recovering an image. The proposed approach offers choice of embedding two watermarks and is able to detect and differentiate the modifications applied on the watermarked image. Semi-fragility makes the scheme tolerant against JPEG lossy compression. While, recovery attribute makes it suitable for video surveillance and remote sensing applications.

Dual watermarking method for secure image authentication and recovery

This paper presents a semi-fragile watermarking technique capable of verifying the authenticity and recovery of the image. The proposed approach has the capability to accurately detect and differentiate modifications applied on the watermarked image. Alteration sensitivity has been improved compared to previous approaches and it can concisely determine the region of the watermarked image where the integrity verification fails. Semi-fragility makes the proposed method tolerant against JPEG lossy compression and other acceptable modifications but sensitive to malicious attacks such as cutting and pasting. The exact low pass version of the image is recovered by using the lossless compression (Huffman coding). Simulation results demonstrate that the alteration sensitivity of the proposed authentication scheme is much better compared to the previous approaches.