基于第二代Curvelet变换的指纹预处理算法

An algorithm for the enhancement of fingerprints was presented;an algorithm for realizing the foreground/background segmentation was also discussed,based on a new mathematical transform,namely, the second generation curvelet transform.The result shows that the algorithm is effective and the transform is attractive.分析了现有的一些增强、分割算法的不足,提出了基于第二代Curvelet变换的指纹图像预处理算法.实验结果表明提出的算法简单有效,能够实现指纹图像增强的要求.

改进的基于区域的运动目标分割方法

针对视频监控系统,提出了一种改进的基于区域的运动目标分割方法。与传统方法相比,在运动检测阶段,结合时域差分和背景差分进行运动检测,并通过自适应方法进行背景更新;在差分图像二值化时,采用自适应阈值方法来代替传统的手工确定阈值法;对于区域分割,使用基于加权平方欧式距离的均值聚类算法代替传统的均值聚类算法。实验结果表明该改进方法比传统方法具有更好的实时性、鲁棒性和有效性。

Elliptic Object Detection Based on Shape Preserving and Active Contour

本文通过形状约束方程(组)与一般主动轮廓模型结合,将目标形状与主动轮廓模型融合到统一能量泛函模型中,提出了一种形状保持主动轮廓模型即曲线在演化过程中保持为某一类特定形状。模型通过参数化水平集函数的零水平集控制演化曲线形状,不仅达到了分割即目标的目的,而且能够给出特定目标的定量描述。根据形状保持主动轮廓模型,建立了一个用于椭圆状目标检测的统一能量泛函模型,导出了相应的Euler-Lagrange常微分方程并用水平集方法实现了椭圆状目标检测。此模型可以应用于眼底乳头分割,虹膜检测及相机标定。实验结果表明,此模型不仅能够准确的检测出给定图像中的椭圆状目标,而且有很强的抗噪、抗变形及遮挡性能。

The Effect of Periodic Segmentation Cracks on the Interfacial Debonding: Study on Interfacial Stresses

Hard coatings on relatively soft substrate always face the danger of debonding along the interface. Interfacial stresses are considered to be the initial driving force for the interfacial debonding of the relatively strong bonded coatings. Interfacial stresses due to the mismatch of strain between the coating and substrate are simulated with FEM firstly. The distribution of the interfacial stresses is achieved, which confirms an excessive stresses concentration near the interface end. Subsequently, the redistribution of interfacial stresses is calculated for a coating with periodic segmentation cracks. Results indicate that the distribution of interfacial stresses is altered greatly with the periodic segmentation cracks. To reveal the effect of the spacing of the periodic segmentation cracks on the distribution of interfacial stresses, different crack density is modeled within the coating. It is found that that the peak values of the interfacial stresses decrease with the increase of crack density, i.e. with reduction of spacing of segmentation cracks.

On the Formation of Periodic Segmentation Cracks in a Coating Plated on a Substrate with Periodic Subsurface Inclusions

The mechanism of the formation of periodic segmentation cracks of a coating plated on a substrate with periodic subsurface inclusions (PSI) is investigated. The internal stress in coating and subsequently the strain energy release rate (SERR) of the segmentation cracks are computed with finite element method (FEM). And the effect of the geometrical parameters of the PSI is studied. The results indicate that the ratio of the width of the inclusion to the period of the repeated structure has an optimum value, at which the maximum internal tensile stress and SERR arise. On the other hand, the ratio of the max-thickness of the inclusion to the thickness of the coating has a threshold value, above which the further increase of this ratio should seldom influence the internal stress or the SERR.

On The Interaction Of Channeling/Segmentation Cracks Of Coating: Study On The Critical Spacing

Channeling/segmentation cracks may arise in the coating subjected to in-plane tensile stress. The interaction between these multiple cracks, say the effect of the spacing between two adjacent cracks oil the behaviors of channels themselves and the interface around the interface corners, attracts wide interest. However, if the spacing is greater than a specific magniture,, namely the Critical Spacing (CS), there should be no interaction between such channeling/segmentation cracks. In this study, file mechanism of the effect of the crack spacing oil the interfacial stress around the interface corner will be Interpreted firstly. Then the existence of the CS will be verified and the relationship between the CS and the so-called stress transfer length Ill coating will be established for plane strain condition. Finally, the dependence of the stress transfer length, simultaneously of the CS, on the sensitive parameters will be investigated with finite element method and expressed with a simple empirical formula. (C) 2007 Elsevier Ltd. All rights reserved.

Novel approach for region merging and image segmentation for human-computer interaction

For the purpose of human-computer interaction (HCI), a vision-based gesture segmentation approach is proposed. The technique essentially includes skin color detection and gesture segmentation. The skin color detection employs a skin-color artificial neural network (ANN). To merge and segment the region of interest, we propose a novel mountain algorithm. The details of the approach and experiment results are provided. The experimental segmentation accuracy is 96.25%. (C) 2003 Society of Photo-Optical Instrumentation Engineers.

Spatiotemporal segmentation based on two-dimensional spatiotemporal entropic thresholding

A novel spatiotemporal segmentation technique is further developed for extracting uncovered background and moving objects from the image sequences, then the following motion estimation is performed only on the regions corresponding to moving objects. The frame difference contrast (FCON) and local variance contrast (LCON), which are related to the temporal and spatial homogeneity of the image sequence, are selected to form the 2-D spatiotemporal entropy. Then the spatial segmentation threshold is determined by maximizing the 2-D spatiotemporal entropy, and the temporal segmentation point is selected to minimize the complexity measure for image sequence coding. Since both temporal and spatial correlation of an image sequence are exploited, this proposed spatiotemporal segmentation technique can further be used to determine the positions of reference frames adaptively, hence resulting in a low bit rate. Experimental results show that this segmentation-based coding scheme is more efficient than usual fixed-size coding algorithms. (C) 1997 Society of Photo-Optical Instrumentation Engineers.

The Effects of Visual Object Size in The Depth Perception in KM Mouse

Whether mice perceive the depth of space dependent on the visual size of object targets was explored when visual cues such as perspective and partial occlusion in space were excluded. A mouse was placed on a platform the height of which is adjustable. The platform located inside a box in which all other walls were dark exception its bottom through that light was projected as a sole visual cue. The visual object cue was composed of 4x4 grids to allow a mouse estimating the distance of the platform relative to the grids. Three sizes of grids reduced in a proportion of 2/3 and seven distances with an equal interval between the platform and the grids at the bottom were applied in the experiments. The duration of a mouse staying on the platform at each height was recorded when the different sizes of the grids were presented randomly to test whether the Judgment of the mouse for the depth of the platform from the bottom was affected by the size information of the visual target. The results from all conditions of three object sizes show that time of mice staying on the platform became longer with the increase in height. In distance of 20 similar to 30 cm, the mice did not use the size information of a target to judge the depth, while mainly used the information of binocular disparity. In distance less than 20 cm or more than 30 cm, however, especially in much higher distance 50 cm, 60 cm and 70 cm, the mice were able to use the size information to do so in order to compensate the lack of binocular disparity information from both eyes. Because the mice have only 1/3 of the visual field that is binocular. This behavioral paradigm established in the current study is a useful model and can be applied to the experiments using transgenic mouse as an animal model to investigate the relationships between behaviors and gene functions.

The application of DBF neural networks for object recognition

On the basis of DBF nets proposed by Wang Shoujue, the model and properties of DBF neural network were discussed in this paper. When applied in pattern recognition, the algorithm and implement on hardware were presented respectively. We did experiments on recognition of omnidirectionally oriented rigid objects on the same level, using direction basis function neural networks, which acts by the method of covering the high dimensional geometrical distribution of the sample set in the feature space. Many animal and vehicle models (even with rather similar shapes) were recognized omnidirectionally thousands of times. For total 8800 tests, the correct recognition rate is 98.75%, the error rate and the rejection rate are 0.5% and 1.25% respectively. (C) 2003 Elsevier Inc. All rights reserved.

Object-recognition with oblique observation directions based on biomimetic pattern recognition

In this paper, we propose a new scheme for omnidirectional object-recognition in free space. The proposed scheme divides above problem into several onmidirectional object-recognition with different depression angles. An onmidirectional object-recognition system with oblique observation directions based on a new recognition theory-Biomimetic Pattern Recognition (BPR) is discussed in detail. Based on it, we can get the size of training samples in the onmidirectional object-recognition system in free space. Omnidirection ally cognitive tests were done on various kinds of animal models of rather similar shapes. For the total 8400 tests, the correct recognition rate is 99.89%. The rejection rate is 0.11% and on the condition of zero error rates. Experimental results are presented to show that the proposed approach outperforms three types of SVMs with either a three degree polynomial kernel or a radial basis function kernel.