Earticle

This paper analysis the prediction structure based on layered B frame used by multi view video coding, introduces the common predictive structure and their evaluation index, proposes a kind of improved prediction structure, and makes comparative analysis on the performance of encoding time, PSNR and code rate by experiment which uses the typical test sequences Ball-room and Exit provided by MERL on the multi view video coding test platform. The experimental results show that: the improved prediction structure showed better coding efficiency; coding complexity reduction is up to 15%, the better to improve the real-time performance of code.

This work presents the comparison of various multicarrier based Pulse Width Modulation (PWM) techniques for the chosen single phase CMLI (Cascaded Multi Level Inverter). In this paper, a single phase symmetrical cascaded multilevel inverter is controlled with sinusoidal, THI (Third Harmonic Injection), Trapezoidal, TAR (Trapezoidal Amalgamated Reference) and Stepped Wave reference with Equal Amplitude Carriers (EAC) and UEAC (Un Equal Amplitude Carriers). The proposed EAC and UEAC are applied for various PWM strategies. The PWM methods used for the analysis are PD (Phase Disposition) PWM, POD (Phase Opposition and Disposition) PWM, APOD (Alternative Phase Opposition and Disposition) PWM, CO (Carrier Overlapping) PWM, PS (Phase Shift) PWM and VF (Variable Frequency) PWM with EAC and UEAC. For all the PWM methods and references the UEAC produces less THD and higher fundamental RMS (Root Mean Square) values except for ma =1. For ma =1 the EAC provides less THD (Total Harmonic Distortion) and higher fundamental RMS (Root Mean Square) values for all the PWM methods and references. To validate the developed technique, simulations are carried out through MATLAB/SIMULINK.

Friction and wear process is due to the interaction of the relative motion between friction pair surfaces. Problems of rough surface and contact mechanics are not just appeared in tribology, but they have close relationship with friction or tribology and they are the necessary problem to solve in understanding of friction and wear phenomena. In the paper, we make the assumption of deformation continuity and smoothness of the surface asperity and combined with related theory to establish a mathematical model for the calculation for surface contact. The model is verified with a specified example. The results have been calculated and compared with results of other models. The comparison results show that the calculation model established in this paper has small error when the load is small load but with big difference with test results when the load is higher. The model can be used in the research of influence factors of real contact area of sliding friction surface, but it should take actual factors into consideration.

To realize Frequency Shift Keying (FSK) decoding and Dual-Tone Multi-Frequency (DTMF) dialing, a novel hardware and software solution is presented. These two signals are used to receive or send messages respectively in this solution which can meet different requirements of many Public Switched Telephone Network (PSTN) applications. The hardware used CPC5622 as the phone line interface Data access arrangement (DAA), HT9032D as the FSK decoder, and C8051f120 as the DTMF generator and system controller. The software, mainly composed of DTMF dialing and FSK decoding subprograms, was written and debugged with the hardware and finally succeeded to realize the terminal. The results performed under Huawei C&C08 switch show that the terminal can realize dialing by encoding standard DTMF signals and extracting the caller's information from the standard FSK signals in the PSTN. The CPC5622 as well as C8051f120 has some free Inputs, outputs, and other hardware resources, which make the PSTN terminal scalable and available to a variety of PSTN devices and applications.

This paper demonstrates the comparison of 40 Gbps DWDM system using hybrid optical amplifier configurations (EDFA-EDFA and EDFA-SOA ) are implemented with RZ and NRZ encoding techniques at various distance along with DCF having dispersion -80 ps/nm/Km . DWDM systems with 4 channels each having a bit rate of 10 Gbps and 0.8 nm equal channel spacing. The performance of EDFA-EDFA and EDFA-SOA hybrid optical amplifiers with different modulation formats (NRZ and RZ) are evaluated in terms of BER, eye height and Q-factor. EDFA-EDFA performed better upto 200 km as compared to EDFA-SOA optical amplifiers at 100 km distance with NRZ format. For RZ format EDFA-EDFA performance of DWDM system is also good upto 250 km as compared to EDFA-SOA upto 120 km. In this paper, DWDM system using EDFA-EDFA yields better result than EDFA-SOA and also for RZ encoding technique communication is achieved more distance than NRZ encoding technique.

With high definition cameras are widely used in urban traffic monitoring, the resolution of vehicle and traffic monitoring image rises. As the main component of intelligent traffic system, the vehicle license plate recognition technique faces new challenges and some new demands are put forward. Aiming at the problems of cutting down the time delay and eliminating characters outside of vehicle license plate, a set of license plate recognition algorithm is developed in this paper. The process of recognition in this paper is divided into four parts: image preprocessing, license plate location, license plate segmentation and character recognition. In license plate location, an accelerating matching method based on particle image correlation method is employed. In character recognition, an improved BP neural network algorithm is employed. The principle, procedure and simulation of the algorithm is described in details. High definition images with 2 mega pixels are used as the input of simulation.

All phase digital filter (APDF) is a new type of linear phase FIR digital filter which was proposed in recent years, and a general method to design 2-D FIR digital filters called 2-D APDF is presented in this paper. Firstly, the theory of biorthogonal wavelet transform and 2-D APDF is expounded. Secondly, a novel algorithm is proposed to implement biorthogonal wavelet transform by using 2-D APDF based on DFT and IDCT. The relations between two kinds of filters are discussed. As an important application of biorthogonal wavelet transform, multi-resolution analysis of 2-D image signal could be used to test the feasibility and applicability of the proposed algorithm. Finally, the test image can be reconstructed perfectly in the multi-resolution analysis of 2-D image experiment using MATLAB tool in this paper, and the analysis indicates that the proposed method performs well.

The design of phase frequency detector (PFD) using CMOS current mode logic (CML_PFD) is presented in this paper. Further its performance has been compared with a proposed PFD, denoted here as M_CML_PFD. The simulation results are focused on accounting the power dissipation, delay and output noise. Both the PFDs are designed to be dead zone free and using 0.35μm CMOS technology on SPICE simulator. The output noise experienced is reduced by 6.5% in M_CML_PFD. The power dissipation of the proposed M_CML_PFD is 15.72% lesser and delay is 2.37 times less than the CML_PFD when operating at 100 MHz input frequency with 3.3V voltage supply.

As the Microsoft’s Kinect sensor can generate a real-time dense depth map with relatively commercial available, it is widely used in depth map capturing. However, there are some artifacts like holes, instability of the raw input data, which seriously affect the application. To solve this problem, in this paper, we propose a novel depth map refinement method based on by GMM and CS theory which enable the kinect sensor generate a dense depth map, the background large holes are filled without blurring, and the edges of the objects are sharpened, median filter is used to remove noise. Experiments on captured indoor data demonstrate the effectiveness of the method especially in the edge area and occlusion area that our method can obtain better results.

In recent years, several researches have been conducted on spectral clustering to classify non-linear data in various applications. Considering the effect of selecting the appropriate eigenvectors on spectral clustering performance; various methods have been proposed weighting and ranking features. However, these methods can independently evaluate the impact of each eigenvector. Nevertheless, it is possible that several eigenvectors have duplicate or inadequate information on some clusters. Thus, we have presented a new method for finding the optimal combination of eigenvectors by several different evaluation criteria. In order to detect simultaneously the optimum condition in various criteria, the multi-objective genetic algorithm is applied. Findings of performed experiments on datasets with various features demonstrate a resounding success in the proposed method.

Aiming at the problems that current skin-color detection segmentation technologies have unsatisfied segmentation results under conditions of complex illumination or backgrounds, we present a new method based on YCbCr color space and K-means clustering algorithm for segmentation hand gesture. Firstly, image in RGB color space is converted to YCbCr color space; and then YCbCr color space of image is divided into luminance Y and chrominance Cb and Cr. Lastly, the binary image is achieved by clustering values of chrominance using k-means clustering algorithm, and hand gesture segmentation is completed by conducting morphological process of binary image obtained. The experimental results illustrate that the proposed method can segment hand gestures from complex backgrounds and obtain segmentation results. The phenomena of similar skin color interference and skin color overlapping are solved with this method effectively. In addition, it is robust to illumination condition.

A new method of energy distribution estimation in the joint time-frequency domain using the Channelized Instantaneous Frequency (CIF) and Local Group Delay (LGD) is proposed. The signal energy distribution is estimated by discarding and displacement of energy parts. The signal energy leads to high concentrated distribution in the time-frequency domain due to the relocation of the CIF and LGD values. In addition to this, a channelized instantaneous bandwidth and local group duration are used to remove undesired energy part. The channelized instantaneous bandwidth and local group duration express a local stretching of the signal in frequency and time respectively. This method is being used for speech signal analysis.

The scalable extension to the H.264/AVC has been established as a scalable video coding (SVC) standard, and JPEG2000 is a state of the act still image coding standard. The most distinctive difference between SVC and JPEG2000 is, in terms of spatial-frequency transformation, that SVC is based on the Discrete Cosine Transform (DCT) and JPEG2000 is based on Discrete Wavelet Transform (DWT). JPEG2000 outperforms its predecessor-JPEG which adopts DCT by nearly 30% in terms of compression performance. Despite the DWT has been successfully employed in still image coding, the latest video coding standard keeps on ultilising DCT and the relevant techniques as its coding tools. In this paper, we investigate SVC for intra frame coding and JPEG2000 for still image coding, on video sequences with different resolutions and features. From the experimental evaluations, we attempt to gain deeper insight into the application scenarios of these two transform techniques. The experimental results demonstrate that at high bitrates, JPEG2000 outperforms SVC, and it is vice versa. We also note that the PSNR difference between SVC and JPEG2000 decreases with increasing the picture resolution. Therefore, JPEG2000 is more suited for high definition picture compression. The spatial scalability of SVC and JPEG2000 is also investigated in the evaluation, and the results show that SVC gains quite better performance than JPEG2000.

Watermarking is an art in which we hide some secret information in another file like image, audio, video, text etc. Watermarking is a concept closely related to steganography. In these, both hide information in a digital image. The information hide in this is in different forms like an image, song, video within the signal itself. In this paper, we present survey on image watermarking. In this paper, we also explain the types of watermarking and various techniques of watermarking and requirements of digital watermarking. We survey on some papers of image watermarking.

For the system that can’t be described by the precise mathematical model and has long time delays, the conventional Smith predictor presents poor stability and large overshoot. Based on the conventional Smith predictor, an improved fuzzy adaptive PID-Smith predictor is proposed. It uses a fuzzy self-tuning PID controller as the primary controller instead of the traditional PID controller. In addition, a feedback loop and an adaptive regulator are imported to ensure the stability and enhance the adaptability of the variable environment. The simulation results show that the new scheme has excellent stability and robustness and can solve the problem of large overshoot in long time delay systems, even when the model mismatch rate comes to 40%.

The accurate segmentation and extraction of bamboo cross-section image has a vital role on bamboo processing automation. The Lab color space in accordance with the color features of the bamboo wood cross-section is chosen in this paper. The bamboo cross-section image segmentation and extraction algorithm based on the clustering theory is proposed. The algorithm firstly takes advantage of the character that the colors represented by channel a and channel b of the Lab color space accord with the color of the bamboo wood, to be combined feature vector. Then the algorithm uses the k-mean clustering algorithm to classify the eigenvectors to realize the segmentation of the bamboo wood cross-section. At last the circle fitting algorithm is used to realize the final frame of the bamboo wood cross-section. The results of the experiments show that the algorithm can be used to realize the complete segmentation of the cross-section image of bamboo wood, and to frame the results correctly, the time performance of which can meet the requirements of the subsequent processing.

Adaptive filters are commonly used to remove disturbances corrupting a signal, particularly when a reference signal correlated to the disturbance is available. Accompanying random noise, sinusoidal disturbance or other undesired signals can be removed from the desired signal. When applied to images, the term adaptive filter commonly refers to a filter which changes its features based on the local statistical characteristics of the image and noise (within each image segment). It has also been proposed previously to use the LMS adaptive filter for 2-D image filtering, mostly for random noise removal. In this paper, it is offered to extend the use of the 2-D LMS adaptive filter to other image disturbances, such as a varying frequency sinusoidal disturbance, and the removal of an undesired added image from the desired one. Moreover, it is proposed here that in some cases it may be useful to convert the two-dimensional image to a one-dimensional signal (by chaining its row or columns), and apply a 1-D LMS adaptive filter. The 2-D LMS adaptive filter is demonstrated to work well in restoring an image corrupted by a random noise, a sinusoidal disturbance or a disturbance of an undesired image added to the desired one. In some particular conditions an adaptive filter with no reference signal may also be used to remove the undesired disturbance from the image.

Transmission accuracy of traditional Transmission Control Protocol (TCP) in high-bandwidth wireless network is low, and its efficiency is low. For these problems, the thesis proposes a virtual router model from the perspective of end-to-end, and on this basis of using the classical control theory the thesis proposes an end-to-end PI rate control algorithm--SPI RCP on the transmitter. According to the RTT information collected by the transmitter, the real-time queue length of virtual router is calculated, and by using the PI control theory the transmission rate of the transmitter is calculated to make the queue length of the bottleneck node is stabilized at a target location, at the same time to avoid the wrong adjust of congestion windows caused by wireless link packet loss. The end-to-end design of new algorithm saves router resources, enhances the stability of the queue length, and reduces network congestion packet loss. The simulation results show that compared with the traditional congestion control protocol, the new mechanism can better control the queue length of the router and improve the stability and network throughput of the network load.

Due to limited depth of field of machine vision cameras, multifocused image fusion is finding importance to produce a single image called fused image from various images of the same scene being imaged. To have focused images of all the objects in the scene, the fused image is formed by combining important features of various images. This in turn increases the importance of ability to assess the quality of the fused image more accurately. To be accurate, a typical image quality measure should be independent of image content, robust to noise, monotonic with respect to image blur and calculated with minimal computation complexity. In this paper, the performance of nine image quality measures were assessed through various experiments by applying image blur, adding image noise, changing image contrast and image saturation level. Experiments were also conducted on six sets of images to find the best image quality measure for multifocused image fusion.

Content-aware image retargeting has drawn much attention in image and vision research in recent years. However, existing methods are very difficult to ensure that the result images from retargeting achieve good visual effect on the whole, since these methods mainly focus on spatial image information. In this paper, we propose a new approach on content-aware image retargeting based on visual effect assessment. We establish an evaluation mechanism of the visual effects of retargeted images which is based on a priori statistical knowledge through studying the user's evaluation, and build the computable model of visual effect assessment of retargeted image with the help of mathematical description from Dynamic Bayesian Networks. After finishing content-aware processing and construct a three-level model of visual saliency contents for the original image, we retarget the original image into the target image by virtue of deforming image, and integrate computable model of visual effect assessment into retargeting process, so as to guide the retargeting. Finally, by steadily adjusting the size of the intermediate results from deforming image, we make this size be eventually equal to the size of the target image of retargeting, under the constraint that the result image should acquire good visual effect through optimizing the parameters of visual effect assessment. Real data have been used to test the proposed approach and very good results have been achieved, validating it.

In the process of analyzing scientific research ability on music, many problems present, including that indicators are not comprehensive enough, the model has much subjectivity, the evaluation results are not reliable or the value of quantity of indicators has errors. Thus, this paper proposes a grey relational analysis model of scientific research ability on music based on AHP. It selects out dominant indicators and recessive indicators to evaluate software features and hardware features. A multi-layer evaluation index system for scientific research ability on music is established. AHP is introduced to compute the weight of indicators. After standardization of indicators, a multi-scheme grey relational coefficient model and a grey relational degree model are established according to grey theory to evaluate the level of scientific research ability on music. Proved effective by the case study, this model can realize the evaluation of scientific research ability on music on the computer.

Image fusion is an important branch of information fusion, widely used in various fields, especially in medical field. So increasing the quality and efficiency of medical image fusion has great significance. Combining the advantages of pulse coupled neural networks with Compressive Sensing; this paper puts forward a novel image fusion method in NSCT transform domain. First, NSCT transform is applied to the source images, and the coefficients in low frequency coefficient are fused by mean rules. For high frequency coefficient, CS is applied and PCNN. Finally, inverse NSCT is applied to get the reconstructed image. The experimental results show that the fusion algorithm proposed in this paper in the performance and integration efficiency has better fusion results.

The phase-locked amplifier with output stability can filter out the noise effectively and the weak signal will be extracted from the noise and be amplified. The signal processing is relatively simple, so it is an effective way to detect the weak signal. It uses the phase sensitive detector (Phase Sensitive Detection, PSD) technique to identify the test signal, which has same frequency with the reference signal, and eliminate the interference noise signal of different frequency, so as to accurately measure the size of the measured signal. In this paper, switching correlator is taken as a core part of lock-in amplifier with large dynamic range, strong anti-overload and no non-linear problems. Moreover, lock-in amplifier output signal amplitude has no impact from the amplitude of the reference .

An improved SLIC method using uniform segmentation and reciprocal nearest neighbor (RNN) clustering is presented in this paper. This approach is made of two steps. First, image is segmented to a large number of regular homogeneous and small regions which are similar to cell. Second, instead of the original image pixels, small regions segmented are regarded as input of RNN clustering. A new similarity criterion is decided by regional diversity of average value normalized and variance. Regional constraint filter limited the large size of superpixel guarantees the uniformity and compactness of superpixel. Finally, the regions in a small range of distance are merged by RNN clustering. Results of experiment on BSDS 500 dataset of natural images show the proposed method has advantages of high boundary recall and low under-segmentation error over SLIC on small numbers superpixel.

In this paper, the performance of fixed-gain amplify-and-forward (FAF) relaying is investigated. An approximation for the average symbol error probability (SEP) is derived for multiple-mobile-relay-based mobile-to-mobile (M2M) cooperative networks over N-Nakagami fading channels. The moment generating function (MGF) method is used to obtain average SEP expressions for various modulation techniques. The performance under different conditions is evaluated through numerical simulation to verify the analysis. These results show that the number of mobile relay nodes, the fading coefficient, the number of cascaded components, the relative geometrical gain, and the power allocation parameter have a significant impact on the SEP performance.

In today’s scenario security of data is very big challenge in any communication. Numerous data security and hiding algorithms have been developed in the last decade. The Digital image Steganography is science of hiding sensitive information in another transmission medium to achieve secure and secret communication. In this paper we present the dual layer of security to the data, in which first layer is to encode data using Least Significant Bit image steganography method and in the second layer encrypt the data using Advance Encryption Standard Algorithm. Steganography does not replace the encryption of data, instead it provides extra security feature to it. In our work secret text message is hiding behind the digital image file and this image file is then encrypted using AES encryption algorithm.

Stroke is a common condition among the elderly in high latitude and cold area. Its high occurrence, recurrence and disability rate makes it a serious threat for the health and life of middle to old age population, and a heavy burden for patient’s family and the society as a whole. Surface electromyogram signal is a bio-electricity signal recorded from electrodes on muscle surface with controlled neuromuscular actions. It is a direct signal revealing muscle activity and function, and it can reflect neuromuscular activity to certain extent. This study focuses on the accumulated data of electromyographic signal recorded from human upper limb, using Matlab tool to analyze and compare neuromuscular signals between healthy population and stroke patients, finding characters of surface neuromuscular signals with mathematical methods such as Fourier transformation, Hilbert transformation and AR modelling, and then induce the changing pattern of neuromuscular signals with various physiological indicators and make prediction of muscular pathological tendency.

In order to solve the issue of embedded image processing, a method of mixed compression for RGB565 format true color image is proposed. According to the inherent correlation of image data, the method adopts the discrete cosine transform and rearrangement to centralize the data that have higher correlation. Finally, it achieves the image compression by improving the run-length coding combined with statistical coding. Experiments show that the method can compress the true color images with RGB565 format effectively on the platform of ARM-Linux, and achieve a good compression ratio.

A visual system based on virtual and real video for the humanoid robot manipulation is presented. 3D virtual model of humanoid robot is established. It has the same aspect and freedom setup as the real robot. Multiple feedback from the robot are fused and used to express the real robot status as text and images. The system also forecasts the operation order and displays the simulation result. In the data fusion module, a least-squares algorithm is adopted to calculate the real-time position and attitude of the robot. Experiments demonstrate that the system can offer good telepresence and a preview of the operation order. In this paper, we also propose an adaptive Elastic Net method for edge linking of images from the robot cameras to understand the situation of the task. In the proposed method, an adaptive dynamic parameter strategy and a stochastic noise strategy are introduced into the Elastic Net, which enables the network to have superior ability for escaping from local minima and converge sooner to optimal or near-optimal solutions