Securing Fingerprint Images Through PSO Based Robust Facial Watermarking

This paper presents an efficient hybrid watermarking scheme for securing fingerprint images in the Discrete Cosine Transform (DCT) domain. The proposed method uses a NN-PSO (Neural Network-Particle Swarm Optimization) based hybrid approach to watermark host gray scale fingerprint images with their corresponding facial images in order to secure them. The algorithm divides the input image into blocks and uses a feed forward NN to determine the number of secret bits to be embedded in each block depending on the blocks' features. The output of the NN is then used as input by the PSO module to find the best DCT coefficients' locations in that block where the secret facial image data can be embedded, so that the distortion produced in the host image is minimum and the minutia predicting ability remains unaffected. The experimental results have been analyzed and compared with existing PSO based and NN based approaches. The proposed NN-PSO based hybrid approach has been found to exhibit better watermarked image quality and better robustness to possible attacks to the watermarked image. Moreover, as the proposed technique retains the feature set of the original fingerprint, the extracted facial image and the cover fingerprint image can be correctly verified at the receiver's end leading to a more secure and accurate biometric based personal authentication.

Biometric Systems (BS) are commonly used to recognize individuals based on biological characteristics such as fingerprints, iris, ears, face, signatures, veins, typing styles gaits, and voices. Uni-modal BS does not have improved protection or recognition accuracy, so multi-modal BS is implemented. However, multi-modal BS has several disadvantages, including intra-class differences, non-universality, Spoof attacks, and distinctiveness. To address these problems, this paper proposes a multimodal biometric image watermarking scheme based on Particle Swarm Optimization (PSO). The sharpening filter is used in this method for image enhancement, resulting in an effective input image for authentication. For face and finger vein feature value extraction, Empirical Mode Decomposition (EMD) technique is used. For fingerprint feature value extraction, minutiae extraction methodology is used. For combining the feature, feature level fusion is used. The main concept of proposed technique is to use a fingerprint image and demographic data to watermark an individual's face and finger vein image. For embedding the watermark, PSO is used to select the best Discrete Cosine Transform (DCT) coefficients in the face and finger vein image. PSO's objective feature is focused on capacity of human visual perception and the watermarked image's ability to withstand image processing attacks. When the watermark is removed on the receiver's hand, the functional utility of biometrics is preserved, resulting in a more secure.KeywordsBiometricsMultimodalPSOWatermarkingSecurityAuthentication

When host images are watermarked with CRT (Chinese Remainder Theorem), the watermark images are still robust in spite of the damage of the host images by maintaining the remainders in an unchanged state within some range of the changes that are incurred by the attacks. This advantage can also be attained by "zero-watermarking," which does not change the host images in any way. This paper proposes an improved zero-watermarking scheme for color images on the DCT (Discrete Cosine Transform) domain that is based on the CRT. In the scheme, RGB images are converted into YCbCr images, and one channel is used for the DCT transformation. A key is then computed from the DC and three low-frequency AC values of each DCT block using the CRT. The key finally becomes the watermark key after it is combined four times with a scrambled watermark image. When watermark images are extracted, each bit is determined by majority voting. This scheme shows that watermark images are robust against a number of common attacks such as sharpening, blurring, JPEG lossy compression, and cropping.

-With developing of computer networks and digital techniques, the electronic image are easily created, edited, reproduced and distributed. Unfortunately, illegal copy and malicious tamper are also facilitated. At present, fragile watermark is researched greatly to authenticate the veracity and integrity of electronic contents. In this paper, a chaotic watermarking scheme for authentication of popular JPEG images is proposed. The quantized DCT ( Discrete Cosine Transform ) coefficients after entropy decoding are mapped to the initial values of the chaotic system, then the generated watermark information by chaotic iteration is embedded into JPEG compressed domain. Thanks to the high sensitivity on initial values of the chaotic mapping, the very accurate localization is realized for the malicious tampers to JPEG images. Because we directly modify the DCT coefficients after quantization for embedding the watermark, the proposed method can prevent the invalidation of tamper detection by JPEG re-quantization. Furthermore, because the proposed scheme avoids a large of computation on full decoding and re-encoding process, the low complexity and a high extracting speed are obtained. Simulation results show the proposed scheme can directly localize the tampers happened on the watermarked JPEG images. Furthermore, the ability of tamper localization is very sensitivity. So the proposed scheme is very fit for the integrity authentication of the electronic image in Internet.

At recently, the most of the digital images are stored and transferred in their compressed format using discrete cosine transform (DCT)-based compression technique. DCT is one of the most important data compression technique due to the efforts from Joint Photographic Experts Group(JPEG). Blind steganalysis means how to detect the presence of the messages that are hidden using different types of steganography algorithms and has the ability to detect new unknown steganography algorithms. This paper presents blind steganalysis technique that can reliably detect the existence of messages hidden in JPEG files. In order to save the computation and memory cost, it is desirable to have image processing operations implemented directly in the DCT domain. The proposed method is based on extracting features directly from DCT domain through the analysis of differences between DCT coefficients before and after cropping. The extracted features are prepared as input to Support Vector Machine (SVM) to classify the image as stego (image that contain secret message) or clean (image that does not contain secret message). The experiments performed show that the proposed method yields better classification accuracy compared with other related works.

워터마킹은 소유권을 주장하기 위하여 워터마크라는 디지털 신호를 영상에 첨가하는 것이다. 본 논문에서는 기존의 DCT를 이용한 디지털 워터마킹 방법을 개선하여 비가시성과 견고성을 동시에 향상시키는 새로운 DCT 기반의 디지털 워터마킹 방법을 제안한다. 제안한 방법에서는 원 DCT 계수의 상대적 중요성이 워터마킹된 DCT 계수에서도 보존되며, 원 DCT 계수의 왜곡을 최소화시키는 워터마크 재정렬 방법을 이용함으로서 비가시성과 견고성을 향상시킨다. 실험을 통하여 제안한 방법은 기존의 워터마킹 방법보다 비가시성을 약 9～12[dB] 향상시키며, 다양한 공격에 대해 견고성이 월등히 우수함을 확인하였다. Watermarking is embedding a digital signal called as watermark into images to claim the ownership. In this paper, a new digital watermarking algorithm based on DCT (Discrete Cosine Transform) which enhances invisibility and robustness is proposed to improve contentional digital watermarking method using DCT. In the proposed method, it is possible to enhance invisibility and robustness using watermark reordering in which the relative significance of original DCT coefficients can be preserved in watermarked DCT coefficients, and the distortions of original DCT coefficients can be minimized. The experimental results show that the proposed method improves invisibility approximately 9～12[dB] and is more robust to various attacks than the conventional method.

Many effective watermarking algorithms have been proposed and implemented for digital images and digital video. However, a few algorithms have been proposed for audio watermarking. This is due to the fact that, human auditory system (HAS) is far more complex and sensitive than human visual system (HVS). In this research work, a new method of embedding image data into the audio signal and additive audio watermarking algorithm based on Discrete Cosine Transformation (DCT) domain is proposed. First, the original audio is transformed into DCT domain. The DCT coefficients are divided into a fixed number of subsections and the energy of each subsection is calculated. Next, watermark is generated from image by image processing algorithm. Watermarks are then embedded into selected peaks of highest energy subsection. Experimental results demonstrate that the watermark is inaudible and this algorithm is robust to common operations of digital audio signal processing, such as noise addition, re-sampling, requantization and so on. To evaluate the performance of the proposed audio watermarking method, subjective and objective quality tests including Bit Error Rate (BER) and Signal to Noise ratio (SNR) are conducted.

With the wide use of various image altering tools, digital image manipulation becomes very convenient and easy, which makes the detection of image originality and authenticity significant. Among various image tampering detection tools, double JPEG image compression detector, which is not sensitive to specific image tampering operation, has received large attention. In this paper, we propose an improved double JPEG compression detection method based on noise-free DCT (Discrete Cosine Transform) coefficients mixture histogram model. Specifically, we first extract the block-wise DCT coefficients histogram and eliminate the quantization noise which introduced by rounding and truncation operations. Then, for each DCT frequency, a posterior probability can be obtained by solving the DCT coefficients mixture histogram with a simplified model. Finally, the probabilities from all the DCT frequencies are accumulated to give the posterior probability of a DCT block being authentic or tampered. Extensive experimental results in both quantitative and qualitative terms prove the superiority of our proposed method when compared with the state-of-the-art methods.

A gray-level intensity image can be employed as a host image for hiding a watermark image to protect information security. Past research works demonstrate that a gray-level hidden image can be embedded into the host image by a digital phase-only holography method. However, the fidelity of retrieved watermark image from the host image is not very satisfactory and the host image quality is degraded due to the insertion of external data bits, especially when observers focus on the saliency regions in the host image. To address this problem, we propose a steganography method based on digital holography and the saliency map of the host image. First, we calculate the hidden capacity (number of bits to be replaced) for each host image pixel based on the weighted sum of pixel intensity and saliency value. Next, a multilevel phase-only digital hologram of the watermark image will be calculated by the Gerchberg–Saxton method under the constraint of the hidden capacity of host image. Finally, we embedded the multilevel phase-only digital hologram into the host image by replacing a corresponding number of bits in each pixel. In this way, the host image can preserve good image fidelity for its saliency regions even if we hide a large amount of digital hologram data into the host image. The experimental results show that the quality of retrieved watermark image from the host image and the quality of saliency regions in the watermarked host image, in our proposed scheme, are superior to the state-of-the-art works reported.

This paper presents new fast full search motion estimation (ME) algorithms using discrete cosine transform (DCT) coefficients as a gradient magnitude. The proposed algorithms use intra DCT coefficients to arrange the matching scan order. The proposed algorithm 1 uses some of DCT coefficients based on the relationship between gradient magnitude and DCT coefficients, and the proposed algorithm 2 uses all of DCT alternating current (AC) coefficients in order to predict the fluctuation of a block. The proposed algorithms significantly reduce the computational complexity of the conventional algorithm while maintaining the visual quality of video.

디지털 워터마킹은 저작권 보호와 멀티미디어 데이터 인증의 수단으로 사용되어 왔다. 기존의 공간영역에서의 CRT 기반 워터마킹 방법은 JPEG 압축에 취약하여, JPEG 압축에서 잘 동작하는 DCT 영역에서의 CRT 기반 워터마킹이 제안되었다. 본 논문에서는 DCT 영역에서의 향상된 CRT 기반 워터마킹 방법을 제안한다. 제안한 방법은 DCT 변환시 발생되는 rounding 오류 또는 여러 가지 공격에도 나머지들의 차에 대한 절대값의 변화를 감소시켜 견고성을 향상시킨다. 실험을 통하여 제안한 방법이 기존의 DCT 영역에서의 CRT 기반 워터마킹 방법보다 여러 가지 공격에 대하여 견고성이 향상되는 것을 확인하였다. Digital watermarking techniques have been used as one of the means for copyright protection and authentication of multimedia data. Conventional Chinese Remainder Theorem(CRT)-based spatial domain watermarking techniques do not perform well under JPEG compression. However, it is seen that the CRT-based watermarking technique in Discrete Cosine Transform(DCT) domain performs well for JPEG compression. In this paper, an improved CRT-based image watermarking method in the DCT domain is proposed. The proposed method provides better robustness which decreases changes of absolute difference of residues against rounding errors due to DCT conversion and various attacks. Experimental results show that the proposed method has a good robustness against various attacks compared with the conventional CRT-based watermarking in DCT domain.

Digital watermarking is an encryption technique commonly used to protect intellectual property and copyright. Although watermarks are a robust method of protecting property rights, environmental interference in image propagation through the Internet is inevitable, and human-based image modification can also destroy watermarks. In this study, watermarks (affected by noise interference) were embedded in a 256ź×ź256 pixel host image by using the discrete cosine transform (DCT) technique, which transfers the spatial domain of the host image into the frequency domain. Subsequently, 32ź×ź32 pixel watermarked images were embedded as watermark identification codes in the transferred frequency-domain-based host image. The inverse discrete cosine transform (IDCT) technique was used to alter the frequency of the spatial domain, thereby allowing the host image to be visible to the human eye. Several common interferences, such as salt-and-pepper noise, Gaussian noise, clipping, and rotation, were used to destroy the watermarked image. After the destruction process, the watermark was almost discernible in a slightly damaged state, but difficult to identify in a seriously damaged state after using the DCT watermarking scheme. In this study, a back-propagation neural network (BPNN) algorithm combined with a DCT watermarking scheme was used to suppress the interference affecting watermarks. The simulation results of using the proposed DCT-BPNN method indicated that the original watermarked image was restored considerably after being subjected to environmental interference during image propagation.

In this paper, a new block matching criterion is proposed for motion estimation in video coding. The new criterion is based on a comparison between the discrete cosine transform (DCT) coefficients of two blocks to be matched. Since the spectrum of DCT statistically concentrates on the neighborhood of the dc component and the number of non-zero coefficients is quite small, only few coefficients need to be considered when matching blocks according to the new criterion. Almost in all the video coding standards, DCT is a necessary step for spatial redundancy reduction. Thus the generated DCT coefficients can be utilized in the new criterion. However, there are still some blocks whose DCT coefficients are not available. Several algorithms of calculating DCT coefficients of these blocks are given. When this new criterion is combined with the logarithm search, promising results are produced.

Security and authentication of the people information is effectively provided through various watermarking algorithms. Most of the conventional watermarking algorithms have their own drawbacks in maintaining the quality and security of the image against various attacks. In order to overcome the above stated issues, a watermarking technique based on optimization is required for preserving image quality. In this paper, singular value decomposition (SVD) based digital image watermarking (DIW) scheme is proposed in hybrid discrete cosine transform (DCT) and discrete wavelet transform (DWT) using optimization algorithms like particle swarm optimization (PSO) and Jaya algorithm. The watermark image (WI) is embedded into low frequency DWT sub-band of DCT of cover image. PSO and Jaya algorithms are applied to improve the security threats and quality by assessing the fitness function. The work involves in utilizing the feature points in embedding of watermarks and analyzing the impact of various types of attacks with respect to image quality. The performance parameters like peak signal to noise ratio (PSNR), Structural Similarity Index (SSIM) and correlation coefficient of fitness function given by PSO and Jaya algorithm.

The performance and effectiveness of CBIR scheme are directly associated with construction of small dimensional as well as salient image features respectively. So, in this paper, we have carried out the image retrieval process with small dimensional salient Image components or features as compare to the original image size and the imaze retrieval accuracy has been improved due to the consideration of local information rather than global information of Image data. Initially, the Image data is exploited in block level by discrete cosine transformation (DCT) and subsequently, some significant DCT coefficients are selected from each block as salient image components. However, all the DCT coefficients are not equally important in terms of visual perception and their dimension is also not negligible even in Image retrieval process. Later, selected AC coefficients are divided into four different groups. Later, some statistical parameters are computed from each group. Each statistical value is placed at a particular matrix. So, from each group, the number of matrices constructed is equal to the number of statistical parameters evaluated and one more matrix for DC coefficients is considered. Further, for construction of small dimensional feature vectors, gray level co-occurrence matrix (GLCM) is employed on all constructed matrices to derive the feature vector for a color component. The same procedure is employed on all three components and all feature vectors are combined toaether to form the final feature vector. The proposed CBIR structure is tested on three standard Image database i.e. Corel-lK, GHIM-10K and Olivia database and the experimental results demonstrate satisfactorily image retrieval and performance outperform other state-of-art schemes in many instances with respect to their precision values.