In order to extract usable harmonics from real 2^(n) sequence pseudo-random data,a technical method is proposed.An equation for predicting the average amplitude of the main frequencies is proposed to guide the choice ...In order to extract usable harmonics from real 2^(n) sequence pseudo-random data,a technical method is proposed.An equation for predicting the average amplitude of the main frequencies is proposed to guide the choice of signal type for different exploration tasks.By the threshold of the amplitude of the transmitted signal,a set of candidate frequencies are first selected.Then,by operating a spectrum envelope method at these candidate frequencies on received data,effective components in data are extracted.A frequency density calculation method is proposed based on a logical number summation method,to reasonably characterize the frequency density in different frequency bands.By applying this method to real data in Sichuan,China,with signal Type 13,75 effective components are extracted,including both main frequencies and harmonics.The result suggests that the number of effective frequencies in the 2^(n) sequence pseudo-random signal can be increased by extracting usable harmonics,without any additional fieldwork.展开更多
In the field of underwater image processing, the line and rounded objects, like mines and torpedoes, are the most common targets for rec, ognition. Before further analysis, these two image patterns need to be detected...In the field of underwater image processing, the line and rounded objects, like mines and torpedoes, are the most common targets for rec, ognition. Before further analysis, these two image patterns need to be detected and extracted from the underwater images in real-time. Using the subpixel position, direction and curvature information of an edge provided by Zernike Orthogonal Moment （ZOM） edge detection operators, an enhanced Randomized Hough Transform （RHT） to extract straight-lines is developed. This line extraction method consists of two steps ： the rough parameters of a line are obtained robustly at first using RHT with large quantization in the Hough space and then the parameters are refined with line fitting techniques. Therefore both the robustness and high precision can be achieved simultaneously. Particularly, the problem of ellipse extraction is often computationally demanding using traditional Hough Transform, since an ellipse is characterized by five parameters. Based on the generalized K-RASAC algorithm, we develop a new ellipse extraction algorithm using the concept of quadratic curve cluster and random sampling technique. We first develop a new representation of quadratic curves, which facilitates quantization and voting for the parameter A that represents a candidate ellipse among the quadratic curves. Then, after selecting two tangent points and calculating the quadratic parameter equation, we vote for the parameter A to determine an ellipse. Thus the problem of ellipse extraction is reduced into finding the local minimum in the A accumulator array. The methods presented have been applied successfully to the extraction of lines and ellipses from synthetic and real underwater images, serving as a basic computer vision module of the underwater objects recognition system. Compared to the standard RHT line extraction method and K-RANSAC ellipse extraction method, our methods have the attractive advantages of obtaining robustness and high precision simultaneously while preserving the merits of high computation speed and small storage requirement.展开更多
In this work,a system for recognition of newspaper printed in Gurumukhi script is presented.Four feature extraction techniques,namely,zoning features,diagonal features,parabola curve fitting based features,and power c...In this work,a system for recognition of newspaper printed in Gurumukhi script is presented.Four feature extraction techniques,namely,zoning features,diagonal features,parabola curve fitting based features,and power curve fitting based features are considered for extracting the statistical properties of the characters printed in the newspaper.Different combinations of these features are also applied to improve the recognition accuracy.For recognition,four classification techniques,namely,k-NN,linear-SVM,decision tree,and random forest are used.A database for the experiments is collected from three major Gurumukhi script newspapers which are Ajit,Jagbani and Punjabi Tribune.Using 5-fold cross validation and random forest classifier,a recognition accuracy of 96.19%with a combination of zoning features,diagonal features and parabola curve fitting based features has been reported.A recognition accuracy of 95.21%with a partitioning strategy of data set(70%data as training data and remaining 30%data as testing data)has been achieved.展开更多
The random decrement technique is an averaging technique that can be used to extract the free decay response of the structure from its random stationary vibratory response. The free decay response can then be used to ...The random decrement technique is an averaging technique that can be used to extract the free decay response of the structure from its random stationary vibratory response. The free decay response can then be used to identify the vibratory characteristics of the structure. The main advantage of the technique is that the identification of the parameters of the structure is achieved without previous knowledge of the excitation forces. This paper extends the random decrement technique to obtain the mode shapes of the structure using the concept of a multichannel random decrement technique （MCRD）. This technique is based on extracting simultaneous random decrement records from measurements made at several points on the structure. The method is very efficient and simple. Numerical examples are solved and compared with the exact mode shapes extracted using classical modal analysis. An excellent agreement between the extracted modes shapes using the MCRD and those obtained from the classical modal analysis techniques is achieved. The vibration of an offshore structure excited by white noise excitation is used to illustrate the method.展开更多
基金financially supported by the National Key Research and Development Program of China(No.2019YFC0604902)the National Natural Science Foundation of China(No.42004056)the Natural Science Foundation of Shandong Province,China(No.ZR201911010111).
文摘In order to extract usable harmonics from real 2^(n) sequence pseudo-random data,a technical method is proposed.An equation for predicting the average amplitude of the main frequencies is proposed to guide the choice of signal type for different exploration tasks.By the threshold of the amplitude of the transmitted signal,a set of candidate frequencies are first selected.Then,by operating a spectrum envelope method at these candidate frequencies on received data,effective components in data are extracted.A frequency density calculation method is proposed based on a logical number summation method,to reasonably characterize the frequency density in different frequency bands.By applying this method to real data in Sichuan,China,with signal Type 13,75 effective components are extracted,including both main frequencies and harmonics.The result suggests that the number of effective frequencies in the 2^(n) sequence pseudo-random signal can be increased by extracting usable harmonics,without any additional fieldwork.
文摘In the field of underwater image processing, the line and rounded objects, like mines and torpedoes, are the most common targets for rec, ognition. Before further analysis, these two image patterns need to be detected and extracted from the underwater images in real-time. Using the subpixel position, direction and curvature information of an edge provided by Zernike Orthogonal Moment （ZOM） edge detection operators, an enhanced Randomized Hough Transform （RHT） to extract straight-lines is developed. This line extraction method consists of two steps ： the rough parameters of a line are obtained robustly at first using RHT with large quantization in the Hough space and then the parameters are refined with line fitting techniques. Therefore both the robustness and high precision can be achieved simultaneously. Particularly, the problem of ellipse extraction is often computationally demanding using traditional Hough Transform, since an ellipse is characterized by five parameters. Based on the generalized K-RASAC algorithm, we develop a new ellipse extraction algorithm using the concept of quadratic curve cluster and random sampling technique. We first develop a new representation of quadratic curves, which facilitates quantization and voting for the parameter A that represents a candidate ellipse among the quadratic curves. Then, after selecting two tangent points and calculating the quadratic parameter equation, we vote for the parameter A to determine an ellipse. Thus the problem of ellipse extraction is reduced into finding the local minimum in the A accumulator array. The methods presented have been applied successfully to the extraction of lines and ellipses from synthetic and real underwater images, serving as a basic computer vision module of the underwater objects recognition system. Compared to the standard RHT line extraction method and K-RANSAC ellipse extraction method, our methods have the attractive advantages of obtaining robustness and high precision simultaneously while preserving the merits of high computation speed and small storage requirement.
文摘In this work,a system for recognition of newspaper printed in Gurumukhi script is presented.Four feature extraction techniques,namely,zoning features,diagonal features,parabola curve fitting based features,and power curve fitting based features are considered for extracting the statistical properties of the characters printed in the newspaper.Different combinations of these features are also applied to improve the recognition accuracy.For recognition,four classification techniques,namely,k-NN,linear-SVM,decision tree,and random forest are used.A database for the experiments is collected from three major Gurumukhi script newspapers which are Ajit,Jagbani and Punjabi Tribune.Using 5-fold cross validation and random forest classifier,a recognition accuracy of 96.19%with a combination of zoning features,diagonal features and parabola curve fitting based features has been reported.A recognition accuracy of 95.21%with a partitioning strategy of data set(70%data as training data and remaining 30%data as testing data)has been achieved.
文摘The random decrement technique is an averaging technique that can be used to extract the free decay response of the structure from its random stationary vibratory response. The free decay response can then be used to identify the vibratory characteristics of the structure. The main advantage of the technique is that the identification of the parameters of the structure is achieved without previous knowledge of the excitation forces. This paper extends the random decrement technique to obtain the mode shapes of the structure using the concept of a multichannel random decrement technique （MCRD）. This technique is based on extracting simultaneous random decrement records from measurements made at several points on the structure. The method is very efficient and simple. Numerical examples are solved and compared with the exact mode shapes extracted using classical modal analysis. An excellent agreement between the extracted modes shapes using the MCRD and those obtained from the classical modal analysis techniques is achieved. The vibration of an offshore structure excited by white noise excitation is used to illustrate the method.
