彩色图像中纯脸检测与定位的优化算法研究

人脸识别是当前模式识别应用的一个重要领域.在理解当前广泛使用的各种人脸识别算法的基础上,提出了一种基于多方法融合的彩色图像纯脸检测与定位的优化算法.该算法首先通过肤色检测及预处理技术缩小彩色图像人脸检测的搜索区域,然后应用基于物体区域方向的检测平面内任意旋转角度人脸计算方法;并通过二次计算旋转角度的方法来准确确定人脸区域的旋转角度;最后利用积分投影函数找到人脸候选区域中双眼的位置,结合人脸特征在人脸中的比例关系准确确定纯脸的位置.该算法还考虑了人脸侧偏时的情况.实验表明,本方法对平面内任意旋转及双眼存在的侧偏人脸有较好的检测效果,对不同光照条件有较好的鲁棒性.     

基于投影匹配的钢坯端面字符快速识别方法

由于高温及复杂光照的干扰等成像环境的影响,钢坯端面字符自动识别存在很多困难,其实时自动识别难度大。现存的字符识别方法难以适应实际生产现场的需求。文章提出了一种基于投影匹配的快速识别方法,通过将图象二值化后进行垂直投影,直接将一维投影结果进行模板匹配,降低运算维数。大量的现场实验证明,该方法可有效的减少识别时间,提高生产效率,字符的拒识率和误识率较低,可满足生产线的实时要求。     

Matlab遗传算法工具箱在非线性优化中的应用

投影寻踪是一种降维处理技术,通过它可以将多维分析问题通过投影方向转化为一维问题分析。应用该法的关键在于寻求最佳投影方向,这可以转化为一个复杂的非线性优化问题来进行解决。选取某地区大气环境质量评价的投影寻踪评价模型,编制相关的目标函数和约束函数,应用基于MATLAB的遗传算法和直接搜索工具箱进行优化求解。结果表明：该工具箱在求解此类非线性优化问题上的有效性和方便性,从而为各领域应用投影寻踪模型提供了强有力的优化工具。     

基于混合多维云模型的工业绿色发展水平测度

如何测度各省工业绿色发展水平高低, 判断各省工业绿色创新能力差异, 本文从绿色投入要素和绿色产出效益视角构建集结综合属性值的工业绿色发展多指标评价体系; 并在云模型基础上提出了基于混合多维云模型的区间多属性测度方法. 该方法创新性地利用区间权重和云权重的相互转换, 在解决多指标权重不一的问题后, 再运用父云贴近度计算工业绿色发展水平, 云投影度测定工业绿色创新能力; 最后采用省际间的工业面板数据进行验证. 结果表明, 相较于一般的多指标综合评价法, 该测定方法的实证结果与实际情况更相符合, 说明了该方法既能对工业绿色发展水平的整体情况进行评价分析, 也能精确计算出各指标贡献度, 从而判断其是否具有工业绿色创新能力. 因此, 本研究可为各地区调整工业绿色发展水平测度指标、制定工业绿色发展规划提供实质性建议和理论决策依据.     

薄透镜成象快速调节技术

本文结合象差理论,分析了薄透镜成象的几个先路图,介绍了相应的快速调节技术．     

LPP solution schemes for use with face recognition

Locality preserving projection (LPP) is a manifold learning method widely used in pattern recognition and computer vision. The face recognition application of LPP is known to suffer from a number of problems including the small sample size (SSS) problem, the fact that it might produce statistically identical transform results for neighboring samples, and that its classification performance seems to be heavily influenced by its parameters. In this paper, we propose three novel solution schemes for LPP. Experimental results also show that the proposed LPP solution scheme is able to classify much more accurately than conventional LPP and to obtain a classification performance that is only little influenced by the definition of neighbor samples.     

Weighted and extended total variation for image restoration and decomposition

In various information processing tasks obtaining regularized versions of a noisy or corrupted image data is often a prerequisite for successful use of classical image analysis algorithms. Image restoration and decomposition methods need to be robust if they are to be useful in practice. In particular, this property has to be verified in engineering and scientific applications. By robustness, we mean that the performance of an algorithm should not be affected significantly by small deviations from the assumed model. In image processing, total variation (TV) is a powerful tool to increase robustness. In this paper, we define several concepts that are useful in robust restoration and robust decomposition. We propose two extended total variation models, weighted total variation (WTV) and extended total variation (ETV). We state generic approaches. The idea is to replace the TV penalty term with more general terms. The motivation is to increase the robustness of ROF (Rudin, Osher, Fatemi) model and to prevent the staircasing effect due to this method. Moreover, rewriting the non-convex sublinear regularizing terms as WTV, we provide a new approach to perform minimization via the well-known Chambolle's algorithm. The implementation is then more straightforward than the half-quadratic algorithm. The behavior of image decomposition methods is also a challenging problem, which is closely related to anisotropic diffusion. ETV leads to an anisotropic decomposition close to edges improving the robustness. It allows to respect desired geometric properties during the restoration, and to control more precisely the regularization process. We also discuss why compression algorithms can be an objective method to evaluate the image decomposition quality.     

The evaluation of speckle contrast with variable speckle generator

Abstract— While laser projection has many advantages, there is a problem with speckle patterns generated as a result of interference of the laser beam and results in bad effects to observers. In 2010, a variable speckle generator, which produces an angular shift of incident light to the screen and generates variable speckle patterns, was suggested. In this study, the performance of a variable speckle generator by using a volume phase holographic beam shaper and scanning mirror was investigated in detail by evaluating both the objective and subjective speckle contrast. The morphology of the speckle pattern was also investigated when the variable speckle generator was activated. With a scanning VPH beam shaper, the objective speckle was effectively reduced because each point of the VPH beam shaper generated different speckle patterns and coherency among each pattern disappeared by using the scan process. On the other hand, subjective speckle was also dramatically reduced by changing the incident angle on the screen, which resulted in generating variable subjective speckle. It was also shown that the speckle reduction rate by using a variable speckle generator did not depend on the coherent length of a laser by evaluating the normalized speckle contrast against the angular shift on the screen.     

Image correction based on homography in stereoscopic projection display

Abstract— Stereoscopic and autostereoscopic projection‐display systems use projector arrays to present stereoscopic images, and each projector casts one parallax image of a stereoscopic scene. Because of the position shift of the projectors, the parallax images have geometric deformation, which influences the quality of the displayed stereoscopic images. In order to solve this problem, a method based on homography is proposed. The parallax images are pre‐transformed before they are projected, and then the stereoscopic images without geometric distortion can be obtained. An autostereoscopic projection‐display system is developed to present the images with and without calibration. Experimental results show that this method works effectively.     

结合二部图投影与排序的协同过滤

协同过滤是推荐系统中应用最为广泛的方法.提出一类基于二部图一维投影与排序相结合的协同过滤算法,文中采用结构相似进行二部图投影并利用随机游走对节点排序.该方法不仅可以防止冷启动,具有较高准确度,且可扩展性良好.另外,该算法可以避免低覆盖率造成的推荐不准确.算法可以有两类不同的实现,分别是基于项协同过滤的项排序算法和基于用户协同过滤的用户排序算法,在标准数据集MovieLens上的测试表明了算法的有效性.