Moving target recognition has a wide application in varieties of domains and has received more attention in recent years. Among all the recognition methods, optical correlation technology, using hybrid optoelectronic joint transform correlator (HOJTC), has the merits of parallel, large capacity and high-speed, so it is considered as one of the most effective methods for moving target detection. But in the course of detecting, some targets are too small to be recognized by HOJTC. These small targets in cluttered background and strong noise may affect the brightness of the correlation peaks and have a serious influence on target recognition results. In order to solve this problem, this paper applies a wavelet multi-scale edge fusion algorithm which firstly extracts the edge at different scales by wavelet modulus maximum method, and then fuses the detected edge to obtain more edge information of the target. In addition, for the moving distortion problems, taking temporal state of the target as the template can achieve the template update. To prove this method, many detection experiments of small moving targets have been performed with optical correlation method. As an example a small target “boat” taking up only pixels is presented. The recognition results show that the brightness of the correlation peaks is enhanced and the target recognition ratio is increased. The conclusion can be drawn that applying this algorithm in optical correlation method can realize the small moving target recognition successfully and expand the application to scope of optical correlation technology.
Target tracking has a wide application in varieties of domains and has a rapid development at home and abroad, so the research on target tracking is more valuable in recent years. In this paper hybrid optoelectronic joint transform correlator (HOJTC) is implemented for tracking the target, which is considered as one of the most effective methods.But in practical application, the low contrast character of the target and the moving distortion problems between the target and the template may cause the phenomenon of low recognition ratio of HOJTC. In order to solve this problem, a kind of wavelet-based threshold segmentation method is applied to increase the contrast. Through this algorithm the histogram of the image is firstly decomposed into wavelet coefficients at every scale with wavelet basis function Sym4.And then according to segmentation norm and wavelet coefficients, the thresholds can be chosen from the reconstructed histogram. Finally use these thresholds to segment the image into ideal areas. In addition, for the moving distortion problem, taking temporal state of the target as the template can realize the template update.To prove this method, many tracking experiments of low contrast targets have been performed with optical correlation method. As an example a low contrast target "tank" (the gray contrast is less than 2%) is presented. The tracking result shows that the brightness of the correlation peaks is enhanced and the target recognition ratio is increased. The conclusion can be drawn that applying this algorithm in optical correlation method can implement the low contrast target tracking successfully and this algorithm provides an available solution to low contrast target tracking.
Nondestructive determination of Au in gold ornaments mainly takes density method and X ray fluorescence spectrometer with energy dispersion (EDXRF), which exists disadvantages. This paper based on the principle of crystallography, deduced the mathematical relationship between the crystallographic parameters, the density and the impurities content in gold jewelry alloys, then introduced the results by density testing and determination of Ag and Cu by EDXRF into the mathematical relationship, and obtained the gold weight percent in gold jewelry alloys. The results show that obtained the gold weight percent and determination of Au by fire assay are almost consistent, which the error is less than 0.12 %, so establishes a synthesis method of determination of Au by EDXRF and density testing, solves the disadvantages which EDXRF only detects on gold jewelry surface and small area, and density testing cannot detect gold jewelry alloy and demands that jewelry shape is simple, and provides an effective synthesis way for determination of Au in gold jewelry alloys.
The design of engine valve spring generally belongs to multi-objective optimum design. The traditional trying means and the graphical methods are difficult to solve the multi-objective optimization problem, and the traditional multi-objective algorithms have certain defects. The elitist non-dominated sorting genetic algorithm (NSGA-II) is an excellent multi-objective algorithm, which is widely used to solve problems of multi-objective optimization. This method can improve the design quality and efficiency, and it has much more engineering practical value.
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