chap1_3

改进经典的otsu算法，使其适应目标所占图像比例较小的情况，使图像分割方法更具有自适应性 (Improve classic otsu algorithm to achieve image segmentation)

对图像进行旋转和缩放的源代码,支持原图像的抽样处理及任意角度的旋转(The image rotation and scaling in any direction)

信号处理的小波导引：稀疏方法（原书第3版） 《信号处理的小波导引：稀疏方法（原书第3版）》全面论述了稀疏表示的重要概念、技术和应用，反映了该主题在当今信号处理领域所起的关键作用。作者在解释了稀疏的主要概念后将其运用于信号压缩、噪声衰减和逆问题，同时给出了冗余字典、超分辨率和压缩感知中的稀疏表示。 　　本书既可以让应用数学系的学生了解数学公式的工程意义，也可以让计算机及电子工程系的学生了解工程问题的数学描述。对于小波理论与应用的研究人员，本书更是一本极具价值的参考书。(a Wavelet Tour of Signal Processing(Third Edition.The Sparse Way))

对CANNY算子进行改进，其中详细的分析了CANNY算子的原理，已经应用改进的canny算子进行边缘检测，效果较好(CANNY operator improvements, including a detailed analysis of the principle of CANNY operator has been applied to improve the canny operator edge detection, better )

说明：  行人检测HOG+SVM进行图片中行人检测，提供训练用的pos和neg样本，效果还可以；没有SVM工具箱的，压缩包里已经提供了，安装一下即可(Pedestrian detection HOG + SVM for pedestrian detection in pictures, providing POS and neg samples for training, the effect is good; without SVM toolbox, the compression package has been provided, just install it.)

这本是用VC++来实现图像处理的书藉,对于学习图像处理的来说是非常有用的.(This is VC++ to realize image processing books, for learning image processing is very useful.)

本文实现了Retinex算法，支持对图像的去雾灯操作，是一种图像增强的方法。(this paper present a new image strength method-Retinex impliment by opencv)

指纹图像因设备、图像增强处理等原因造成的纹线断裂会产生伪特征点,会对指纹识别产生负面影响。在结 合传统方法优点的同时,针对间距大、方向偏移小和间距大、方向偏移大的断裂情况,本文设计出窗口制约法和改进的 窗口制约法2 种不同的修复方法。实验结果表明,该方法使修复更加全面、完整,提高了伪特征点去除率,易于编程实 现,对细化指纹图像的断裂有很好的修复效果。(The broken ridge fingerprint image processing equipment, image enhancement and other causes will generate pseudo-feature points to be a negative impact on fingerprint identification. While combining the traditional method has the advantage, for the spacing, direction offset small spacing, direction offset large fracture situation, this design window constraints window method and the improved two kinds of constraints, different repair methods. Experimental results show the method to fix a more comprehensive and complete removal of pseudo-feature points, easy to program, well thinned fingerprint image fracture repair.)

角点检测的概述，是一篇文章，介绍了角点检测的发展和现状(coener detection)

混合高斯(Mixture of Gaussian, MOG) 背景建模算法和Codebook 背景建模算法被广泛应用于监控视频的运动目标检测问题, 但混合高斯的球体模型通常假设RGB 三个分量是独立的, Codebook 的圆柱体模型假设背景像素值在圆柱体内均匀分布且背景亮度值变化方向指向坐标原点, 这些假设使得模型对背景的描述能力下降. 本文提出了一种椭球体背景模型, 该模型克服了混合高斯球体模型和Codebook 圆柱体模型假设的局限性, 同时利用主成分分析(Principal components analysis, PCA) 方法来刻画椭球体背景模型, 提出了一种基于主成分分析的Codebook 背景建模算法. 实验表明, 本文算法不仅能够更准确地描述背景像素值在RGB 空间中的分布特征, 而且具有良好的鲁棒性.(The background modeling algorithm of mixture of Gaussian (MOG) and codebook is widely used in moving object detection of surveillance video. However, the ball model of MOG usually assumes that the three components of RGB are independent, while the cylinder model of codebook assumes that the value of background pixel is distributed uniformly within the cylinder and the changing direction of brightness points to the origin of the coordinate system. These assumptions reduce the descriptive capability for background modeling. Therefore, the paper proposes an ellipsoid- based background model, which overcomes the MOG and codebook0s limitations. By using principal component analysis to depict the ellipsoid background model, a novel PCA-based codebook background modeling algorithm is proposed. Experiments show that this algorithm can not only give more accurate description of the distribution of background pixels but also have a better robustness.)