New Dynamic Algorithm for IRFPA Bad Pixel Detection and Compensation Based on Statistics

Based on the analysis to the behavior of bad pixels, a statistics-based auto-detecting and compensation algorithm for bad pixels is proposed. The correcting process is divided into two stages： bad pixel detection and bad pixel compensation. The proposed detection algorithm is a combination of median filtering and statistic method. Single frame median filtering is used to locate approximate map, then statistic method and threshold value is used to get the accurate location map of bad pixels. When the bad pixel detection is done, neighboring pixel replacement algorithm is used to compensate them in real-time. The effectiveness of this approach is test- ed by applying it to I-IgCATe infrared video. Experiments on real infrared imaging sequences demonstrate that the proposed algorithm requires only a few frames to obtain high quality corrections. It is easy to combine with traditional static methods, update the pre-defined location map in real-time.

Sensor scheduling for ground maneuvering target tracking in presence of detection blind zone

Continuous and stable tracking of the ground maneuvering target is a challenging problem due to the complex terrain and high clutter. A collaborative tracking method of the multisensor network is presented for the ground maneuvering target in the presence of the detection blind zone(DBZ). First, the sensor scheduling process is modeled within the partially observable Markov decision process(POMDP) framework. To evaluate the target tracking accuracy of the sensor, the Fisher information is applied to constructing the reward function. The key of the proposed scheduling method is forecasting and early decisionmaking. Thus, an approximate method based on unscented sampling is presented to estimate the target state and the multi-step scheduling reward over the prediction time horizon. Moreover, the problem is converted into a nonlinear optimization problem, and a fast search algorithm is given to solve the sensor scheduling scheme quickly. Simulation results demonstrate the proposed nonmyopic scheduling method(Non-MSM) has a better target tracking accuracy compared with traditional methods.

Blind detection of liquefaction by existing methods for New Zealand M_L6.3 earthquake on Feb. 22,2011

Real-time liquefaction monitoring and warning techniques are new ways to mitigate liquefaction hazard. A key point is to establish a reverse liquefaction detection method based on seismic records. However, the existing methods are quite limited and the reliability requires verification. On Feb. 22, 2011 an earthquake of magnitude 6.3 struck at New Zealand＇s South Island. Remarkable liquefaction phenomena were reported, which provide an opportunity to verify the existing liquefaction detection methods. 27 acceleration records within 50 km to the epicenter were selected to perform a blind detection by using the existing methods, including Miyajima method, Suzuki method, Kostadinov-Yamazaki method and Yuan-Sun method. The blind detection results indicate that Yuan-Sun method gives correct results for seven confirmed sites, and Suzuki method and Yuan-Sun method yield correct detection for a reported non-liquefied site. Four methods including the Yuan-Sun method give identical detection for four sites and three methods also including the Yuan-Sun method give identical detection for ten sites. Besides, there are five sites, for which the four methods give opposite detection.

Science Letters:Blind spot detection using vision for automotive applications

This paper describes a vision-based system for blind spot detection (BSD) in intelligent vehicle applications. A camera is mounted in the lateral mirror of a car with the intention of visually detecting cars that are located in the so-called blind spot and cannot be perceived by the vehicle driver. The detection of cars in the blind spot is carried out using computer vision techniques, based on optical flow and a double-stage data clustering technique for robust vehicle detection.

Discussion on the application prospect of the transient electromagnetic method based on the dual launcher and mine advanced detection

The dual transmitter implements the equivalent anti-magnetic flux transient electromagnetic method, which can effectively reduce the scope of the transient electromagnetic detection blind area. However, this method is rarely reported in the detection of pipelines in urban geophysical exploration and the application of coal mines. Based on this, this paper realizes the equivalent anti-magnetic flux transient electromagnetic method based on the dual launcher. The suppression effect of this method on the blind area is analyzed by physical simulation. And the detection experiment of underground pipelines is carried out outdoors. The results show that the dual launcher can significantly reduce the turn-off time, thereby effectively reducing the impact of the blind area on the detection results, and the pipeline detection results verify the device’s effectiveness. Finally, based on the ground experimental results, the application prospect of mine advanced detection is discussed. Compared with other detection fields, the formation of blind areas is mainly caused by the equipment. If the dual launcher can be used to reduce the blind area, the accuracy of advanced detection can be improved more effectively. The above research results are of great significance for improving the detection accuracy of the underground transient electromagnetic method.

A VERTICAL LAYERED SPACE-TIME CODE AND ITS CLOSED-FORM BLIND SYMBOL DETECTION

Vertical layered space-time codes have demonstrated the enormous potential to accommodate rapid flow data. Thus far, vertical layered space-time codes assumed that perfect estimates of current channel fading conditions are available at the receiver. However, increasing the number of transmit antennas increases the required training interval and reduces the available time in which data may be transmitted before the fading coefficients change. In this paper, a vertical layered space-time code is proposed. By applying the subspace method to the layered space-time code, the symbols can be detected without training symbols and channel estimates at the transmitter or the receiver. Monte Carlo simulations show that performance can approach that of the detection method with the knowledge of the channel.

RLS and LMS blind adaptive multi-user detection method and comparison in acoustic communication

RLS and LMS blind adaptive multi-user detection algorithm and multi-user detector was proposed to solve the problem of multi-user signal detection problem encountered in underwater acoustic communication networks.In simulation analysis,RLS and the LMS blind adaptive multi-user detector were designed and tested for synchronous and asynchronous multi-user communication process.The results of SIR comparison and MMSE comparison show that,both of the two methods can realize blind adaptive detection when any user change in multi-user communication,during this process,the training communication sequences are not needed.The RLS algorithm has about 5 dB higher in SIR compared with LMS algorithm,and the convergence velocity of RLS algorithm is also higher than LMS algorithm when the communication users change.RLS algorithm has better ability in multi-user detection than that of LMS algorithm,and it has great attraction and guiding significance for solving the problem of multiple access interference(MAI) in multi-user communication.

How crystal configuration affects the position detection accuracy in pixelated molecular SPECT imaging systems?

It is well known that inter-crystal scattering and penetration(ICS-P) are major spatial resolution limiting parameters in dedicated SPECT scanners with pixelated crystal.In this study,the effect of ICS-P on crystal identification in different crystal configurations was evaluated using GATE Monte Carlo simulation.A ^(99m)Tc pencil-beam toward central crystal element was utilized.Beam incident angle was assumed to vary from 0° to 45° in 5° steps.The effects of various crystal configurations such as pixel-size,pixel-gap,and crystal material were studied.The influence of photon energy on the crystal identification(CI) was also investigated.Position detection accuracy(PDA) was defined as a factor indicating performance of the crystal.Furthermore,a set of ^(99m)Tc point-source simulations was performed in order to calculate peak-to-valley(PVR) ratio for each configuration.The results show that the CsI(Na)manifests higher PDA than NaI(TI) and YAP(Ce).In addition,as the incident angle increases,the crystal becomes less accurate in positioning of the events.Beyond a crystal-dependent critical angle,the PDA monotonically reduces.The PDA reaches 0.44 for the CsI(Na) at 45° beam angle.The PDAs obtained by the point-source evaluation also behave the same as for the pencil-beam irradiations.In addition,the PVRs derived from flood images linearly correlate their corresponding PDAs.In conclusion,quantitative assessment of ICS-P is mandatory for scanner design and modeling the system matrix during iterative reconstruction algorithms for the purpose of resolution modeling in ultra-high-resolution SPECT.

BLIND DIFFERENTIAL ADAPTIVE MULTIUSER DETECTION

In this paper, a new blind equalization cost function, termed differential mean output energy (DMOE), was presented, and a new multiuser detection algorithm with variable step size was designed. It is shown through simulation results for a co channel system involving severe MAI that the DMOE algorithm gives significantly enhanced signal to interference ratio (SIR) performance and converges rapidly to the optimum MMSE detector, together with a low computational complexity requirement relative to the recursive least squares (RLS) algorithm. Thus, it is not necessary to switch to the decision directed mode. Moreover, it also exhibits global convergence, and can be used in different interference environment without the requirement of estimating and restricting the surplus energy.

HYBRID INTERFERENCE CANCELLATION SCHEME FOR BLIND MULTIUSER DETECTION IN MULTIPATH FADING CHANNELS

This paper introduces and analyzes a detection scheme for adaptive suppression of Multiuser Access Interference (MAI) and MultiPath Distortion (MPD) for mobile station of DS/CDMA system. The proposed detection scheme may amount to a RAKE receiver structure,wherein each branch is considered as a linear multiuser filter designed under a Linear Constrained Minimum Variance (LCMV) optimization strategy to suppress MAI, followed by a proper combining rule to suppress MPD. The adaptive blind multiuser detecting and optimum combining of the proposed receiver are realized, based on the Least-Mean-Square (LMS) algorithm and an adaptive vector tracking algorithm respectively. Finally, the feasibility of the above two algorithms is proved by the numerical results provided by computer simulation.

AN IMPROVED SUBSPACE TRACKING ALGORITHM FOR BLIND ADAPTIVE MULTIUSER DETECTION

As the Projection Approximation Subspace Tracking with deflation(PASTd) algorithm is sensitive to impulsive noise, an improved subspace tracking algorithm is proposed and applied to blind adaptive multi-user detection. Simulation results show that the improved PASTd algorithm not only remains the properties of the conventional PASTdalgorithm, but also has good Bit Error Rate(BER) performance in impulsive noise environment, thus it can effectively improve the system performance.

In-Vehicle Stereo Vision Systems with Improved Ant Colony Optimization Based Lane Detection: A Solution to Accidents Involving Large Goods Vehicles Due to Blind Spots

This paper presents an in-vehicle stereo vision system as a solution to accidents involving large good vehicle due to blind spots using Nigeria as a case study. In this paper, a stereo-vision system was attached to the front of Large Good Vehicles (LGVs) with a view to presenting live feeds of vehicles close to the LGV vehicles and their distance away. The captured road images using the stereo vision system were optimized for effectiveness and optimal vehicle maneuvering using a modified metaheuristics algorithm called the simulated annealing Ant Colony Optimization (saACO) algorithm. The concept of simulated annealing is strategies used to automatically select the control parameters of the ACO algorithm. This helps to stabilize the performance of the ACO algorithm irrespective of the quality of the lane images captured in the in-vehicle vision system. The system is capable of notifying drivers through lane detection techniques of blind spots. This technique enables the driver to be more aware of what surrounds the vehicle and make decisions early. In order to test the system, the stereo-vision device was mounted on a Large good vehicle, driven in Zaria (a city in Kaduna state in Nigeria), and data were in the record. Out of 180 events, 42.22% of potential accident events were caused by Passenger Cars, while 27.22%, 18.33% and 12.22% were caused by two-wheelers, Large Good Vehicles and road users, respectively. In the same vein, the in-vehicle lane detection system shows a good performance of the saACO-based lane detection system and gives a better performance in comparison with the standard ACO method.

Asynchronous QR-RLS-CMOE Blind Multiuser Detection

The QR-RLS-CMOE algorithm which was applied to synchronous DS/CDMA systems in AWGN channel, is modified and applied to asynchronous DS/CDMA systems in multi-path fading channel in this paper. Computer simulation experiences show that the asynchronous QR-RLS-CMOE (A-QR-RLS-CMOE) blind multiuser detection algorithm can well cancel multiple access interference and overcome multipath fading, and has a good anti-near-far effect in the case of τ<<bT .

A Novel Detection Method for Pavement Crack with Encoder-Decoder Architecture

As a current popular method,intelligent detection of cracks is of great significance to road safety,so deep learning has gradually attracted attention in the field of crack image detection.The nonlinear structure,low contrast and discontinuity of cracks bring great challenges to existing crack detection methods based on deep learning.Therefore,an end-to-end deep convolutional neural network(AttentionCrack)is proposed for automatic crack detection to overcome the inaccuracy of boundary location between crack and non-crack pixels.The AttentionCrack network is built on U-Net based encoder-decoder architecture,and an attention mechanism is incorporated into the multi-scale convolutional feature to enhance the recognition of crack region.Additionally,a dilated convolution module is introduced in the encoder-decoder architecture to reduce the loss of crack detail due to the pooling operation in the encoder network.Furthermore,since up-sampling will lead to the loss of crack boundary information in the decoder network,a depthwise separable residual module is proposed to capture the boundary information of pavement crack.The AttentionCrack net on public pavement crack image datasets named CrackSegNet and Crack500 is trained and tested,the results demonstrate that the AttentionCrack achieves F1 score over 0.70 on the CrackSegNet and 0.71 on the Crack500 in average and outperforms the current state-of-the-art methods.

X-ray detection based on complementary metal-oxide-semiconductor sensors

Complementary metal-oxide-semiconductor(CMOS) sensors can convert X-rays into detectable signals; therefore, they are powerful tools in X-ray detection applications. Herein, we explore the physics behind X-ray detection performed using CMOS sensors. X-ray measurements were obtained using a simulated positioner based on a CMOS sensor, while the X-ray energy was modified by changing the voltage, current, and radiation time. A monitoring control unit collected video data of the detected X-rays. The video images were framed and filtered to detect the effective pixel points(radiation spots).The histograms of the images prove there is a linear relationship between the pixel points and X-ray energy. The relationships between the image pixel points, voltage, and current were quantified, and the resultant correlations were observed to obey some physical laws.

Monitoring and Change Detection along the Eastern Side of Qena Bend, Nile Valley, Egypt Using GIS and Remote Sensing

This Article is set to track and monitor changes through spatial dependence of remote sensing data and GIS analysis, the suggested working method in this research is by sub pixel classification techniques. Change detection is a central task for land cover monitoring by remote sensing. It uses multi temporal image data sets in order to detect land cover changes from spectral discrepancies [1] (Rafael, et al.). It discusses the study perception of the situation in the past as well as the current and finally the future status of changes that land uses in Eastern Qena meander specifically in places of estuary floods, and the most important estuary leading to Qena, and whether these changes in land are used in direction of the mouth of the stream or not, especially that when it happened before, it caused destruction of both activities, urban & agricultural land. It will rely on Landsat images in years of (1972-2012), conduct analysis, different classifications integration with geographic information systems (GIS), and field as well as samples for the accuracy assessment.

Blind multiple watermarking algorithm for audio

To make digital watermarking accomplish several goals, a new method for simultaneously embedding multiple watermarks into the same audio signal is proposed. First, the original audio signal is segmented into frames of appointed lengths and all the element watermarks are encoded to achieve a mixed watermark. Then, the binary bits in the mixed watermark are embedded into the audio frames with the echo hiding technique. The watermark extraction can be performed without an original audio signal. Furthermore, in order to enhance the extraction accuracy and the robustness of the proposed algorithm against common signal manipulations, the autocorrelafion of the power cepstrum is utilized to estimate the echo delays in the watermarked audio frames to extract the mixed watermark and the corresponding decoding method is applied to achieve the element watermarks. Computer simulation results indicate that the proposed scheme has great robustness against common signal manipulations of Mp3 compressing, re-sampling, re-quantizing, low-pass filtering and white noise addition.

Data-Driven Joint Estimation for Blind Signal Based on GA-PSO Algorithm

Without any prior information about related wireless transmitting nodes,joint estimation of the position and power of a blind signal combined with multiple co-frequency radio waves is a challenging task.Measuring the signal related data based on a group distributed sensor is an efficient way to infer the various characteristics of the signal sources.In this paper,we propose a particle swarm optimization to estimate multiple co-frequency"blind"source nodes,which is based on the received power data measured by the sensors.To distract the mix signals precisely,a genetic algorithm is applied,and it further improves the estimation performance of the system.The simulation results show the efficiency of the proposed algorithm.

An effective PN blind estimation reconstruction strategy to solve data reversions interference

In a direct spectrum （DS） system, the PN code can be estimated by analyzing the singular vectors of the received data matrix in order to blind despread in a non-cooperative context. But as there are informa-tion data reversions in the analyzed data matrix, some parts of the estimated PN code may be invertible to the original PN code, which may bring about problems in the following despreading process. In order to solve this problem, a method to well reconstruct the PN code is proposed. This method is based on power detection. The combination scheme which has the maximum power is the best combination scheme that is most suitable to the original PN code. Simulation results show that the method can reconstruct the PN code very well,even if the signal-to-noise ratio is low.

Blind Motion Deblurring for Online Defect Visual Inspection

Online defect visual inspection (ODVI) works while the object has to be static, otherwise the relative motion between camera and object will create motion blur in images. In order to implement ODVI in dynamic scene, it developes one blind motion deblurring method whose objective is to estimate blur kernel parameters precisely. In the proposed method, Radon transform on superpixels determinated the blur angle, and the autocorrelation function based on magnitude (AFM) of the preprocessed blurred image was utilized to identify the blur length. With the projection relationship discussed in this study, it will be unnecessary to rotate the blurred image or the axis. The proposed method is of high accuracy and robustness to noise, and it can somehow handle saturated pixels. To validate the proposed method, experiments have been carried out on synthetic images both in noise free and noisy situations. The results show that the method outperforms existing approaches. With the modified Richardson– Lucy deconvolution, it demonstrates that the proposed method is effective for ODVI in terms of subjective visual quality.