0056357

经典的文本水印算法，实现了别人实现不了的功能，希望大家有所用！(The classic text watermarking algorithm to achieve the functions of others fail to realize, I hope you all have a use!)

Matlab time-frequency analysis supporting the source code of chapter 12, please share

利用数字图像处理软件halocn来进行缺陷检测，附带有之前做工程项目的原图源代码，还有ppt和实验指导书(Halocn using digital image processing software for defect detection, comes with artwork done before the project source code, as well as ppt and experimental instructions)

ITK的脑室图像分割,可以对脑部的图像用itk进行分割，用VTK来进行显示。(the segration of brain of ITK )

程序是基于DSP的数字图像处理技术，可以实现军事滤波，中值滤波和维纳滤波，实现效果较好(The program is a DSP-based digital image processing technology, the military filtering, median filtering and Wiener filtering, better )

Image processing using sobel operator

根据指定字符分割字符串，VC++精选编程源码，很好的参考。(According to the specified character segmentation character string, VC++ select programming source code, a good reference.)

图形图像处理中的平滑处理，可以实现部分的功能，但是还可以继续完善(Graphic image processing smoothing, can achieve some of the functions, but can also continue to improve)

由VC实现画矩形、椭圆和随手画功能，对图像处理人员会有帮助(paintings by VC rectangular, oval and hand painting functions, image processing staff to be helpful)

针对粒子概率假设密度(PH D)滤波算法在虚警、漏检情况下，b标状态估计不稳定和b标可观测性车弱的问题，提出了一种基于序贯融合的粒子PH D滤波方法，利用雷达和红外传感器多目标进行融合跟踪杏基本思想是先对红外传感器进行粒子PH D滤波，丙将红外传感器滤波结果作为雷达的预测值，然后利用P达观测的数据进行更新，这样通过雷达和红外传感器交替上作保证目标状态的可观测性，从滤波器输出结身即可得到目标的状态信息仿真结果表明，在虚警、漏检和密集目标环境下，该方法是有效的和稳健的(The problem of target state estimation instability and observability weakerin the presence offalse alarms and missed detection was deal with. On the basis of sequential fusion, a particleprobabil- ity hypothesis density(PHD) filter for multrsensor multrtarget tracking was proposed. Observed da to collected from the infrared sensor was estimated with the particle PHD filter. Then the results from the filter were set as the radar predicted value by the radar observations. The multrtarget state can be updated to guarantee observing the target state. In this way, the global state is updated at the fusion center. Simulation results show that the proposed algorithm is effective and robust under the false warning, omission and concentrated target environment. )