nirmaf

说明：  将像素点划分为超像素，便于进行图像处理！(Implementing superpixel segmentation)

图像 自动 标注 通过分析 训练集 ，学习 图像 和标注词 之间的关系，得出 之间的关系，得出 一些规则， 然后使用这些规则 自动 推导出 图像 最适合的标注词 ，这些标注词代表了图像的 ，这些标注词代表了图像的 高层 语义信息 。(Automatic image annotation by analyzing the training set, learning image and mark the relationship between words, the relationship between the draw, draw some rules, and then use these rules to automatically derive the most suitable image annotation words, these words represent the image annotation , these words represent the image annotation level semantic information.)

关于雷达系统中目标跟踪程序-检测前跟踪(TBD)(About radar target tracking system program- TBD)

文本数字水印技术极富挑战性. 首先简述了文本的分 类 然后介绍了文本数字水印技术领域的主要研究成果和最新进展,包括基于文档结构、自然语言 处理技术和传统图像水印技术三类方法 从容量,鲁棒性,技术基础等方面比较了现有成果,分析了 各类方法的主要优缺点 最后在总结现有成果的基础上展望了文本数字水印技术的前景,指出了该 技术未来可能的研究重点以及待改进和研究的方向.(Text digital watermarking technology challenging, first outlined text points Class then presents the main findings and the latest developments in the field of text digital watermarking technology, including those based on document structure, natural language Processing technology and traditional method of image watermarking technology categories from the capacity, robustness, technology infrastructure and other aspects of the existing comparative results analyzed The main advantages and disadvantages of various types of methods finally summarize the results on the basis of the existing prospect foreground text digital watermarking technology, pointed out that Technology and possible future research priorities for improvement and research directions.)

三维图像配准中的互信息程序。加入边界处理。(脠媒脦 卢 脥 录 脧帽脜盲 脳 录 脰脨渭脛 禄楼 脨脜脧 垄 鲁 脤脨貌 隆 拢 录 脫脠毛 卤 脽 陆 莽 )

一些matlab图像图像处理例程,骨架,灰度图像梯度,凸壳,细化.(Some image image processing matlab routines, skeleton, grayscale gradient, convex hull, thinning.)

matlab与C++混编的grabcut分割程序，只需画框即可提取目标(grabcut algorithm)

（1）计算图像中每个像素点的LBP模式(等价模式,或者旋转不变+等价模式)。 （2）然后计算每个cell的LBP特征值直方图，然后对该直方图进行归一化处理(每个cell中，对于每个bin,h[i]/=sum,sum就是一副图像中所有等价类的个数)。 （3）最后将得到的每个cell的统计直方图进行连接成为一个特征向量，也就是整幅图的LBP纹理特征向量； 然后便可利用SVM或者其他机器学习算法进行分类识别了。((1) calculate the LBP pattern of each pixel in the image (equivalent mode, or rotation invariant + equivalent mode). (2) then the LBP eigenvalue histogram of each cell is calculated, and then the histogram is normalized (for each cell, for each bin, h[i]/=sum, sum is the number of all the equivalent classes in a pair of images). (3) finally, the statistical histogram of each cell is connected into a feature vector, that is, the LBP texture feature vector of the whole picture. Then, SVM or other machine learning algorithms can be used for classification and recognition.)

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 )

对张正友标定得程序重新详细标注了中文注释，方便初学者尽快入门，在最短的时间内了解程序流程，提高学习效率！(Zhang Zhengyou matlab calibration procedures, in order to facilitate a beginner, a code re-done every detail marked Chinese comments, so that we can understand the flow of the program as soon as possible!)