Vision-based fast location of multi-bar code in any direction

The automatic location of the bar code is a key step in the bar code image recognition system. It is extremely confined that the generalization of the traditional bar code localization algorithms due to the requirements of both direction and quality of bar code, and most of them are only aimed at the single barcode localization. In this paper, we have proposed a novel multi-barcode location algorithm in arbitrary direction based on the accumulation of the linear gray value. First, the line coordinates of the barcode region is determined by the image normalized cross-correlation algorithm. Then the center line of gray value of cumulative distribution is used to analyze the barcode boundary and to determine the number of bar code within the region. Finally, the precise positioning of the barcode region is obtained. The experiments have demonstrated that our proposed method can be used to identify all the bar codes in any area, and automatically locate the bar codes in any direction.

Download Full-text

Squint Model InISAR Imaging Method Based on Reference Interferometric Phase Construction and Coordinate Transformation

Remote Sensing ◽

10.3390/rs13112224 ◽

2021 ◽

Vol 13 (11) ◽

pp. 2224

Author(s):

Yu Li ◽

Yunhua Zhang ◽

Xiao Dong

Keyword(s):

Coordinate Transformation ◽

Cross Correlation ◽

Three Dimensional ◽

Image Distortion ◽

Imaging Method ◽

Phase Ambiguity ◽

Correlation Algorithm ◽

Interferometric Phase ◽

Isar Imaging

The imaging quality of InISAR under squint geometry can be greatly degraded due to the serious interferometric phase ambiguity (InPhaA) and thus result in image distortion problems. Aiming to solve these problems, a three-dimensional InISAR (3D ISAR) imaging method based on reference InPhas construction and coordinate transformation is presented in this paper. First, the target’s 3D coarse location is obtained by the cross-correlation algorithm, and a relatively stronger scatterer is taken as the reference scatterer to construct the reference interferometric phases (InPhas) so as to remove the InPhaA and restore the real InPhas. The selected scatterer needs not to be exactly in the center of the coarsely located target. Then, the image distortion is corrected by coordinate transformation, and finally the 3D coordinates of the target can be accurately estimated. Both simulation and practical experiment results validate the effectiveness of the method.

Download Full-text

Automated Locating Mining-Induced Microseismicity without Arrival Picking by Weighted STA/LTA Traces Stacking

Sustainability ◽

10.3390/su12093665 ◽

2020 ◽

Vol 12 (9) ◽

pp. 3665

Author(s):

Yuanjian Jiang ◽

Pingan Peng ◽

Liguan Wang ◽

Zhengxiang He

Keyword(s):

Optimal Algorithm ◽

Signal To Noise Ratio ◽

Dimensional Space ◽

Engineering Application ◽

Location Accuracy ◽

Low Snr ◽

Automatic Location ◽

Grid Search Method ◽

Location Algorithm

The automatic location of the microseismic source is still a challenging endeavor in the microseismic field. Due to the complexity of the mining environment, the microseismic records collected by different channels vary, and generally have a low signal-to-noise ratio (SNR). Therefore, the automatic location algorithm is required to be robust and accurate. For microseismic records with low SNR, the stack-based method does not need to pick arrival, thus avoiding the large location error caused by picking arrival. However, the traditional stack-based method does not consider the influence of the waveform quality of different stations, which can bring some errors to the location result. In this paper, in order to improve the location accuracy of the traditional stack-based method, we propose a method for weighted STA/LTA traces stacking. First, we established evaluation indicators of waveform quality based on microseismic records. Then, the STA/LTA traces are given weight to stack according to the evaluation indicators. Finally, the maximum value of the stacking function is solved in the four-dimensional space to obtain the source coordinates. In the process of calculation, we use the weighted differential evolution (WDE) optimal algorithm instead of the full grid search method, which greatly improves the calculation efficiency. The blasting experiment and engineering application show that the proposed method is stable and effective, and the location accuracy is higher than the traditional stack-based method and the arrival-based method.

Download Full-text

POWER LAW AND STRETCHED EXPONENTIAL EFFECTS OF EXTREME EVENTS IN CHINESE STOCK MARKETS

Fluctuation and Noise Letters ◽

10.1142/s0219477510000162 ◽

2010 ◽

Vol 09 (02) ◽

pp. 203-217 ◽

Cited By ~ 23

Author(s):

XIAOJUN ZHAO ◽

PENGJIAN SHANG ◽

YULEI PANG

Keyword(s):

Correlation Analysis ◽

Power Law ◽

Extreme Events ◽

Stock Markets ◽

Cross Correlation ◽

Extreme Values ◽

Cumulative Distribution ◽

Stretched Exponential ◽

Cross Correlation Analysis ◽

Chinese Stock Markets

This paper reports the statistics of extreme values and positions of extreme events in Chinese stock markets. An extreme event is defined as the event exceeding a certain threshold of normalized logarithmic return. Extreme values follow a piecewise function or a power law distribution determined by the threshold due to a crossover. Extreme positions are studied by return intervals of extreme events, and it is found that return intervals yield a stretched exponential function. According to correlation analysis, extreme values and return intervals are weakly correlated and the correlation decreases with increasing threshold. No long-term cross-correlation exists by using the detrended cross-correlation analysis (DCCA) method. We successfully introduce a modification specific to the correlation and derive the joint cumulative distribution of extreme values and return intervals at 95% confidence level.

Download Full-text

A Novel Gesture Recognition System Based on CSI Extracted from a Smartphone with Nexmon Firmware

Sensors ◽

10.3390/s21010222 ◽

2020 ◽

Vol 21 (1) ◽

pp. 222

Author(s):

Tao Li ◽

Chenqi Shi ◽

Peihao Li ◽

Pengpeng Chen

Keyword(s):

Frequency Domain ◽

Gesture Recognition ◽

Channel State Information ◽

Cross Correlation ◽

Recognition Accuracy ◽

Correlation Method ◽

Bottom Layer ◽

Recognition System ◽

Channel State ◽

State Information

In this paper, we propose a novel gesture recognition system based on a smartphone. Due to the limitation of Channel State Information (CSI) extraction equipment, existing WiFi-based gesture recognition is limited to the microcomputer terminal equipped with Intel 5300 or Atheros 9580 network cards. Therefore, accurate gesture recognition can only be performed in an area relatively fixed to the transceiver link. The new gesture recognition system proposed by us breaks this limitation. First, we use nexmon firmware to obtain 256 CSI subcarriers from the bottom layer of the smartphone in IEEE 802.11ac mode on 80 MHz bandwidth to realize the gesture recognition system’s mobility. Second, we adopt the cross-correlation method to integrate the extracted CSI features in the time and frequency domain to reduce the influence of changes in the smartphone location. Third, we use a new improved DTW algorithm to classify and recognize gestures. We implemented vast experiments to verify the system’s recognition accuracy at different distances in different directions and environments. The results show that the system can effectively improve the recognition accuracy.

Download Full-text

Identification of the State of Electrical Appliances with the Use of a Pulse Signal Generator

Energies ◽

10.3390/en14030673 ◽

2021 ◽

Vol 14 (3) ◽

pp. 673

Author(s):

Augustyn Wójcik ◽

Piotr Bilski ◽

Robert Łukaszewski ◽

Krzysztof Dowalla ◽

Ryszard Kowalik

Keyword(s):

Measurement System ◽

Cross Correlation ◽

Pulse Signal ◽

Signal Generator ◽

Experimental Results ◽

The Novel ◽

End User ◽

Standard Classification ◽

Electrical Appliance

The paper presents the novel HF-GEN method for determining the characteristics of Electrical Appliance (EA) operating in the end-user environment. The method includes a measurement system that uses a pulse signal generator to improve the quality of EA identification. Its structure and the principles of operation are presented. A method for determining the characteristics of the current signals’ transients using the cross-correlation is described. Its result is the appliance signature with a set of features characterizing its state of operation. The quality of the obtained signature is evaluated in the standard classification task with the aim of identifying the particular appliance’s state based on the analysis of features by three independent algorithms. Experimental results for 15 EAs categories show the usefulness of the proposed approach.

Download Full-text