Journal of Harbin Engineering University 

About: Journal of Harbin Engineering University is an academic journal published by Harbin Engineering University. The journal publishes majorly in the area(s): Finite element method & Nonlinear system. It has an ISSN identifier of 1006-7043. Over the lifetime, 1332 publications have been published receiving 3317 citations. The journal is also known as: Journal of Harbin Engineering University.

Digital Computation of Fractional Fourier Transform

Abstract: Based on the concept of the fractional fourier transform, its digital computation is given through computer simulation. In terms of linear frequency modulation (LFM) signal, the relation between fractional order and modulation slope is analyzed and the performance comparison with matched filter is given. Moreover, the separation of LFM signal and noise is realized in low signal-to-noise ratio through simulation. Simulation results indicate that the energy of LFM signal will be collected effectively when the fractional order is matching with its modulation slope. In weak signals detection of underwater acoustic domain, we can get high anti-Doppler performance using the Fractional fourier transform algorithm.

Self-adaptive Canny operator edge detection technique

Abstract: When edge detection is performed using a Canny algorithm,the gradient image should be processed with "non-maximum module suppression" and then double thresholds evaluated to detect edgesHowever,the double thresholds are greatly affected by personal experienceExperiments show that the results of edge detection for different images are obviously different if the identical threshold is employed,which restricted the use of Canny algorithm in practiceTo solve this problem,an algorithm is proposed which can adaptively determine the double thresholds based on gradient histogram and minimum interclass varianceWith this algorithm,it can self-adaptively calculate the double thresholds for different images without the necessity to setup any parameter artificiallyFuzzy algorithm is adopted to choose edge pixelsTheory and experiments show that the algorithm is effective and correct

Object location technique for binocular stereo vision based on scale invariant feature transform feature points

Abstract: An object location method was developed based on scale invariant feature transform(SIFT) feature points that is useful for digital image based binocular stereo visionFirst,the SIFT feature vector was introduced,as it has good robustness to changes such as scaling,rotation and visual anglesBy the use of SIFT feature vector matching,objects which had been collected by a binocular stereo vision system were detected in both left and right images,and thus suitable SIFT feature points were foundThen,by choosing matching points,computing the calibrated point's coordinates,and so on,the calibration points of the object could be determinedThese calibration points describe the same spatial locations of objects in the left and right imagesFinally,the three-dimensional coordinates of the calibration points were rebuilt in the camera's coordinate systemThe results show that the method discussed has good robustness and practicability

An improved adaptive genetic algorithm and its application in function optimization

Abstract: To speed up convergence rates and resolve local convergence issues in traditional adaptive genetic algorithms,an improved adaptive genetic algorithm was developed.According to the concentrating degree of fitness of the populations,a kind of adaptive crossover probability and mutation probability were designed in terms of three variables of maximal fitness,minimal fitness and average fitness of the populations,whereby the crossover probabilities and mutation probabilities of the whole populations could be adjusted.Based on this,an improved adaptive genetic algorithm was developed.Simulation results prove that the new adaptive algorithm can converge faster than the unimproved algorithm and is highly effective at avoiding the premature convergence of the adaptive genetic algorithm.

An algorithm for edge detection of gray-scale image based on mathematical morphology

Abstract: On the basis of mathematical morphology,an improved edge detection operator is proposed that uses morphological operations such as dilation,erosion, opening,closing and their combination.The method can detect the edge efficiently and keep the detected edge smooth.Also introduced was the concept of multi-scale.In order to obtain an ideal image edge under the circumstances of existing noise,the size of structuring elements was adjusted.Experiments demonstrate that compared with traditional edge detectors,this edge detector has a good performance of noise reduction and requires fewer calculations,enhancing its practicality.