2D Discrete Cosine Transform Research Articles

Detection of copy-move image forgery based on discrete cosine transform

Since powerful editing software is easily accessible, manipulation on images is expedient and easy without leaving any noticeable evidences. Hence, it turns out to be a challenging chore to authenticate the genuineness of images as it is impossible for human's naked eye to distinguish between the tampered image and actual image. Among the most common methods extensively used to copy and paste regions within the same image in tampering image is the copy-move method. Discrete Cosine Transform (DCT) has the ability to detect tampered regions accurately. Nevertheless, in terms of precision (FP) and recall (FN), the block size of overlapping block influenced the performance. In this paper, the researchers implemented the copy-move image forgery detection using DCT coefficient. Firstly, by using the standard image conversion technique, RGB image is transformed into grayscale image. Consequently, grayscale image is segregated into overlying blocks of m × m pixels, m = 4.8. 2D DCT coefficients are calculated and reposition into a feature vector using zig-zag scanning in every block. Eventually, lexicographic sort is used to sort the feature vectors. Finally, the duplicated block is located by the Euclidean Distance. In order to gauge the performance of the copy-move detection techniques with various block sizes with respect to accuracy and storage, threshold D_similar = 0.1 and distance threshold (N)_d = 100 are used to implement the 10 input images in order. Consequently, 4 × 4 overlying block size had high false positive thus decreased the accuracy of forged detection in terms of accuracy. However, 8 × 8 overlying block accomplished more accurately for forged detection in terms of precision and recall as compared to 4 × 4 overlying block. In a nutshell, the result of the accuracy performance of different overlying block size are influenced by the diverse size of forged area, distance between two forged areas and threshold value used for the research.

Area and Power Efficient VLSI Architecture for Two Dimensional 16-point Modified Gate Diffusion Input Discrete Cosine Transform

The two-dimensional (2D) Discrete Cosine Transform (DCT) is used widely in image and video processing systems. The perception of human visualization permits us to design approximate rather than exact DCT. In this paper, we propose a digital implementation of 16-point approximate 2D DCT architecture based on one-dimensional (1D) DCT and Modified Gate Diffusion Input (MGDI) technique. The 8-point 1D Approximate DCT architecture requires only 12 additions for realization in digital VLSI. Additions can be performed using the proposed 8 transistor (8T) MGDI Full Adder which reduces 2 transistors than the existing 10 transistor (10T) MGDI Full Adder. The Approximate MGDI 2D DCT using 8T MGDI Full adders is simulated in Tanner SPICE for 0.18㎛ CMOS process technology at 100MHZ.The simulation result shows that 13.9% of area and 15.08 % of power is reduced in the 8-point approximate 2D DCT, 10.63 % of area and 15.48% of power is reduced in case of 16-point approximate 2D DCT using 8 Transistor MGDI Full Adder than 10 Transistor MGDI Full Adder. The proposed architecture enhances results in terms of hardware complexity, regularity and modularity with a little compromise in accuracy.

An Illumination Invariant Face Recognition Using 2D Discrete Cosine Transform and Clahe

Automatic face recognition performance is affected due to the head rotations and tilt, lighting intensity and angle, facial expressions, aging and partial occlusion of face using Hats, scarves, glasses etc.In this paper, illumination normalization of face images is done by combining 2D Discrete Cosine Transform and Contrast Limited Adaptive Histogram Equalization. The proposed method selects certain percentage of DCT coefficients and rest is set to 0. Then, inverse DCT is applied which is followed by logarithm transform and CLAHE. Thesesteps create illumination invariant face image, termed as ‘DCT CLAHE’ image. The fisher face subspace method extracts features from ‘DCT CLAHE’ imageand features are matched with cosine similarity. The proposed method is tested in AR database and performance measures like recognition rate, Verification rate at 1% FAR and Equal Error Rate are computed. The experimental results shows high recognition rate in AR database.

A computation and energy reduction technique for HEVC Discrete Cosine Transform

In this paper, a novel computation and energy reduction technique for High Efficiency Video Coding (HEVC) Discrete Cosine Transform (DCT) for all Transform Unit (TU) sizes is proposed. The proposed technique reduces the computational complexity of HEVC DCT significantly at the expense of slight decrease in PSNR and slight increase in bit rate by only calculating several pre-determined low frequency coefficients of TUs and assuming that the remaining coefficients are zero. It reduced the execution time of HEVC HM software encoder up to 12.74%, and it reduced the execution time of DCT operations in HEVC HM software encoder up to 37.27%. In this paper, a low energy HEVC 2D DCT hardware for all TU sizes is also designed and implemented using Verilog HDL. The proposed hardware, in the worst case, can process 53 Ultra HD (7680x4320) video frames per second. The proposed technique reduced the energy consumption of this hardware up to 18.9%. Therefore, it can be used in portable consumer electronics products that require a real-time HEVC encoder. 1

Passive detection of image forgery using DCT and local binary pattern

With the development of easy-to-use and sophisticated image editing software, the alteration of the contents of digital images has become very easy to do and hard to detect. A digital image is a very rich source of information and can capture any event perfectly, but because of this reason, its authenticity is questionable. In this paper, a novel passive image forgery detection method is proposed based on local binary pattern (LBP) and discrete cosine transform (DCT) to detect copy–move and splicing forgeries. First, from the chrominance component of the input image, discriminative localized features are extracted by applying 2D DCT in LBP space. Then, support vector machine is used for detection. Experiments carried out on three image forgery benchmark datasets demonstrate the superiority of the method over recent methods in terms of detection accuracy.

FPGA Implementation of Approximate 2D Discrete Cosine Transforms

Discrete cosine transform (DCT) is frequently used in image and video signal processing due to its high energy compaction property. Humans are able to perceive and identify the information from slightly erroneous images. It is enough to produce approximate outputs rather than absolute outputs which in turn reduce the circuit complexity. Numbers of applications like image and video processing need higher dimensional DCT algorithms. So the existing architectures of one dimensional (1D) approximate DCTs are reviewed and extended to two dimensional (2D) approximate DCTs. Approximate 2D multiplier-free DCT architectures are coded in Verilog, simulated in Modelsim to evaluate the correctness, synthesized to evaluate the performance and implemented in virtexE Field Programmable Gate Array (FPGA) kit. A comparative analysis of approximate 2D DCT architectures is carried out in terms of speed and area.

Skip block based distributed source coding for hyperspectral image compression

Due to the involvement of massive amount of information in processing and transmission operations, reduction of encoder complexity is a key requirement for lossy compression methods of hyperspectral images. Distributed Source Coding (DSC) is the enabling technology which reverses the encoder-decoder complexity and provides error resilience. In this work, for complexity reduction, the adaptability of block based design to spatially varying characteristics is exploited and combined with DSC. Blocks of size 8x8 with Mean Absolute Error (MeanAE) less than 3.0 and Maximum Absolute Error (MaxAE) less than 4 are identified and skipped from coding, and the remaining portion has been 2D (2-Dimensional) DCT (Discrete Cosine Transform)/SPIHT (Set Partitioning in Hierarchical Trees) coded. Skip block based DSC scheme results in variable source statistics and this is handled with rate adaptive Low Density Parity Check (LDPC) codes. This new block based algorithm, together with rate adaptive codes results in better compression with reduced coding complexity. Our experimental results show that skip block based DSC coded scheme, in addition to being very flexible, retains all the desirable features of compared well-known algorithms. This is also highly competitive to 3D-SPIHT, and better than 2D SPIHT both in terms of compression efficiency and classification.

NON-RECURSIVE COMPUTATION OF 8 × 8 2D DCT FOR HIGH ACCURACY AND LOW AREA

This paper presents non-recursive computation equation for 8 × 8 two-dimensional (2D) discrete cosine transform (DCT) along with novel VLSI architecture for direct computation of DCT without transposition memory. All intermediate operations are performed in non-fraction format. Being non-recursive and all intermediate calculations free of fractions, the proposed architecture has excellent accuracy in terms of peak signal-to-noise ratio (PSNR). The architecture is implemented in 0.18-μm CMOS standard cell technology library and prototyped in Field programmable gate array (FPGA) technology for the silicon validation. Implementation result shows that it has low power consumption and low area as compared to the available architectures of 2D DCT. To further increase the accuracy of computations, hardware overhead is very less as only one register and a multiplier bit-widths need to be changed.

Cordic Iterations based Architecture for Low Power and High Quality DCT

Discrete Cosine Transform (DCT) is widely used in image and video compression standards. This paper presents low-power co-ordinate rotation digital computer (CORDIC) based reconfigurable discrete cosine transform (DCT) architecture. All the computations in DCT are not equally important in generating the frequency domain output. Considering the important difference in the DCT co-efficient the number of CORDIC iterations can be dynamically changed to reduce the power of consumption with improved image quality. The proposed CORDIC based 2D DCT architecture is simulated using Modelsim and the experimental results show that our reconfigurable DCT achieves power savings with improved image quality.

깊이 및 텍스쳐 영상 기반의 3D 입체 영상을 위한 워터마킹 알고리즘

3차원 영상을 생성하기 위해 깊이영상과 텍스쳐 영상의 활용이 보편화되면서 이들 영상에 대한 보호도 많은 관심을 받고 있다. 본 논문에서는 깊이와 텍스쳐 영상으로부터 임의의 시점에 생성되는 스테레오 및 다시점 영상의 소유권을 보호하기 위한 워터마킹 기법을 제안한다. 3D 워핑을 이용한 DIBR을 통해서 워터마크가 보존될 수 있도록 대상 영역을 설정한 이후에 2차원 DCT를 통해서 텍스쳐 영상을 주파수 계수로 변환한다. 이 계수의 일부를 양자화하여 워터마크를 삽입한다. 삽입된 워터마크는 확인이 되지 않기 때문에 비가시성을 확인할 수 있었고, 일반적인 영상처리 공격에 의해서 강인함을 확인하였다. Since the depth and texture images have been widely used for generating 3-dimensional stereoscopic image, the security of them have been focused. In this paper, we propose a new watermarking technique for copyright of stereo and multiview images which is generated in an arbitrary viewpoint by depth and texture image. After the mark space is selected for preserving watermark through DIBR (depth-image-based rendering) process which uses 3D warping, the texture image is transformed to the frequency coefficient using 2D DCT (discrete cosine transform). Some parts of them are quantized, which is the corresponding process to watermarking. The embedded watermark is not conformed by eyes, so we identified the invisibility of the proposed method. In case of appling attacks of general image process, we also identified the robustness of it.

BIVARIATEALGEBRAIC INTEGERENCODED ARAI ALGORITHM FOR EXACT COMPUTATION OF DCT

Discrete Cosine Transform (DCT) function is widely used in many standard image and signal processing applications. Error free architectures with high throughput and reduced hardware area is a major concern.This paper surveys and particularly collates all the information available on arai algorithm that uses algebraic integer coded computation.Bivariate Algebraic Integer(AI) encoded 2-D DCT algorithm ensuresquantization noise free implementation of2-D DCT. This algorithm realizes an error-free 2-D DCT without using Final Reconstruction Steps(FRS) between row–column transforms, leading to an 8×8 2-D DCT that is entirely free of quantization errors in AI basis,thereby avoiding the leakage of quantization noise between DCT channels.This architecture has infinite accuracy till the reconstruction step. The architecture enables low-noise high-dynamic range applications in image processing that requires full control of the finite-precision computation of the 2-D DCT. The 2D DCT algorithm is simulated under fourdifferent conditions, on a gray coded 512X512 image, and PSNR value is measured and compared using MATLAB.

Design and Simulation of Dct Chip In Vhdl and Application in Watermark Extraction

The paper presented the design, modeling and chip implementation of 2D Discrete Cosine Transform (DCT) domain for copyright protection of images, as digital watermarking chip. Recent improvement in computational world and the proliferation of the Internet have facilitated and demanded the production and distribution of unauthorized copies of copyrighted digital contents. The research work involved simulations and synthesis of VHDL code utilizing recent FPGA families of Xilinx, SPARTEN 3E. It is achieving the most demanding real-time requirements of some standardized frame resolutions and rates. The simulation and Synthesis results for 8-point DCT implementations indicate operating frequencies of 50 MHz, and 60 MHz for Xilinx ISE Environment and functional check using Modelsim 10.1 b software.

Research and Improvement on HMM-Based Face Recognition

This paper is concerned with face recognition using the hidden Markov model with 2D-discrete cosine transformation observations. The first part of the paper mainly discusses the influence of sampling parameter selection on model training and recognition efficiency and proposes method to increases the model efficiency through selecting optimal combinations of input parameters. In the second part of the paper, we choose the optimal parameters as input data standard for image matching and extend Viterbi algorithm by setting thresholds, the recognition time is reduced by 12.4% on average.

Transcoding resilient video watermarking scheme based on spatio-temporal HVS and DCT

Video transcoding is a legitimate operation widely used to modify video format in order to access the video content in the end-user's devices, which may have some limitations in the spatial and temporal resolutions, bit-rate and video coding standards. In many previous watermarking algorithms the embedded watermark is not able to survive video transcoding, because this operation is a combination of some aggressive attacks, especially when lower bit-rate coding is required in the target device. As a consequence of the transcoding operation, the embedded watermark may be lost. This paper proposes a robust video watermarking scheme against video transcoding performed on base-band domain. In order to obtain the watermark robustness against video transcoding, four criteria based on Human Visual System (HVS) are employed to embed a sufficiently robust watermark while preserving its imperceptibility. The quantization index modulation (QIM) algorithm is used to embed and detect the watermark in 2D-Discrete Cosine Transform (2D-DCT) domain. The watermark imperceptibility is evaluated by conventional peak signal to noise ratio (PSNR) and structural similarity index (SSIM), obtaining sufficiently good visual quality. Computer simulation results show the watermark robustness against video transcoding as well as common signal processing operations and intentional attacks for video sequences.

A Low Power CMOS Imaging System with Smart Image Capture and Adaptive Complexity 2D-DCT Calculation

A novel low power CMOS imaging system with smart image capture and adaptive complexity 2D-Discrete Cosine Transform (DCT) is proposed. Compared with the existing imaging systems, it involves the smart image capture and image processing stages cooperating together and is very efficient. The type of each 8 × 8 block is determined during the image capture stage, and then input into the DCT block, along with the pixel values. The 2D-DCT calculation has adaptive computation complexity according to block types. Since the block type prediction has been moved to the front end, no extra time or calculation is needed during image processing or image capturing for prediction. The image sensor with block type decision circuit is implemented in TSMC 0.18 µm CMOS technology. The adaptive complexity 2D-DCT compression is implemented based on Cyclone EP1C20F400C8 device. The performance including the image quality of the reconstructed picture and the power consumption of the imaging system are compared to those of traditional CMOS imaging systems to show the benefit of the proposed low power algorithm. According to simulation, up to 46% of power consumption can be saved during 2D DCT calculation without extra loss of image quality for the reconstructed pictures compared with the conventional compression methods.

Research on 3D integer SDCT transform and quantisation

Nowadays, the 3D discrete cosine transform (DCT) is applied widely in video coding. But the transform matrix of DCT is expressed with floating-point numbers, so the computational complexity is high, and more system resources are occupied. In addition, the 3D DCT is accomplished by operating 1D DCT to the rows, columns and pages of 3D data successively, which cannot embody the overall space performance of 3D transform well. To overcome these drawbacks, 3D integer submatrix discrete cosine transform (SDCT) method was proposed in the paper. First, several matrix operation methods were defined. Then, the basic principle and calculation method of 3D integer SDCT was deduced in detail. The main idea was to take the 3D data as a whole, and adopt the integer transform matrix instead of the floating-point transform matrix. Finally, the performances of 3D integer DCT operation were analysed, and the experimental results show that the transform effects based on 3D integer SDCT and 3D DCT are very similar.

Control of speech-related facial movements of an avatar from video

Several puppetry techniques have been recently proposed to transfer emotional facial expressions to an avatar from a user’s video. Whereas generation of facial expressions may not be sensitive to small tracking errors, generation of speech-related facial movements would be severely impaired. Since incongruent facial movements can drastically influence speech perception, we proposed a more effective method to transfer speech-related facial movements from a user to an avatar. After a facial tracking phase, speech articulatory parameters (controlling the jaw and the lips) were determined from the set of landmark positions. Two additional processes calculated the articulatory parameters which controlled the eyelids and the tongue from the 2D Discrete Cosine Transform coefficients of the eyes and inner mouth images.A speech in noise perception experiment was conducted on 25 participants to evaluate the system. Increase in intelligibility was shown for the avatar and human auditory–visual conditions compared to the avatar and human auditory-only conditions, respectively. Depending on the vocalic context, the results of the avatar auditory–visual presentation were different: all the consonants were better perceived in /a/ vocalic context compared to /i/ and /u/ because of the lack of depth information retrieved from video. This method could be used to accurately animate avatars for hearing impaired people using information technologies and telecommunication.

A simple VLSI architecture for computation of 2D DCT, quantisation and zig-zag ordering for JPEG

In this paper, a comparative simulation study of Peak Signal to Noise Ratio (PSNR) in JPEG image compression is done using two quantisation tables, one recommended by JPEG committee and another suitable for hardware simplification. Simulation results confirm that quantisation table suitable for hardware simplification can be used for designing JPEG baseline encoder circuitry. We present a simple Finite State Machine (FSM)-based VLSI architecture from Discrete Cosine Transform (DCT) to zig-zag reordering of transformed coefficients for JPEG baseline encoder using quantisation table suitable for less complex hardware design. The proposed architecture is implemented in Xilinx FPGA as well as Synopsys DC.

A novel architecture for fast 2D IDCT decoders, with reduced number of multiplications

This paper presents a new architecture for the fast computation of the 8×8 two dimensional (2D) Inverse Discrete Cosine Transform (IDCT). The key idea of the proposed method is the permanent storage of the Basis Matrices of the 8×8 2D Discrete Cosine Transform (DCT). By exploiting the sparseness property of the 2D DCT coefficient matrix, the computational time decreases as the number of nonzero coefficients decreases. Moreover, by exploiting the symmetry properties inherent in the Basis Matrices, the introduced method reduces the number of multipliers as well as the number of required multiplications. The proposed structure computes all 64 pixel luminance values of an 8×8 block simultaneously. The efficiency of the proposed architecture is validated through simulations.

Face Recognition with Discriminating 3D DCT Coefficients

In this study, we investigate the use of a 3D discrete cosine transform (DCT) for 3D face recognition and present a novel 3D DCT-based feature extraction method with the selection of discriminating coefficients. We apply a 3D DCT on the voxel data, and use transform coefficients as features. Then the most discriminating 3D transform coefficients are selected with the proportion of variance, sequential floating forward selection and sequential floating backward selection methods. After feature selection, the linear discriminant analysis is applied on reduced sized feature vectors. We compare the results of different feature selection methods and show that a hybrid feature selection method has the best performance both in terms of time and recognition. Our experimental results verify that the discriminating DCT coefficients increase the face recognition rate more than the low-indexed coefficients do. On the other hand, the discriminating coefficients have only an energy level of 1.58%, too low when compared with the total energy of low-indexed coefficients. This fact shows that the discriminating coefficients are not the most energetic ones. With these coefficients, a recognition rate of 99.25% is achieved and this result is compared with other methods tested on a 3D RMA face database.