| 1. | We make doppler beam sharpening ( dbs ) for the receive signal of every sub - aperture , then make difference image
先对每个子天线接收到的信号进行成像处理，然后利用信号的幅相信息进行对消处理。 |
| 2. | Among the face tracking algorithm , we first use difference image to gain the raw - location , then in the limited position , we use two template matching to tracking face
在人脸跟踪的算法中，采用了在差分图像粗定位的基础上，在一个确定的小范围内利用双模板匹配进行跟踪。 |
| 3. | The change detection process performed by unsupervised techniques is usually divided into three main sequential steps : pre - processing , image comparison ( to generate difference image ) and analysis of the difference image
非监督图象变化检测过程通常可以分为预处理、图象比较(得到差异图象)和差异图象分析三个步骤。 |
| 4. | Image difference is the most direct change detection method for change area extraction , but the gray difference image that is only based on spectral feature is difficult in describing the structure change of an objects
图像差分是实现变化区域检测的最直接方法,但是仅仅根据地物光谱特征差异得到的灰度差分图像难以表征地物局部结构的变化。 |
| 5. | Then the scheme based on red eye effect , difference image and kalman filter is adopted . this paper pay attention to introduce the designing of system , the hardware development for capturing image , and algorithms of detection & tracking of pupil
本文完成了该系统的总体设计，开发了视频图像的获取硬件，研究了瞳孔检测与跟踪的算法，并应用此系统进行了实验。 |
| 6. | Then the noise is removed by means of the variance that is estimated directly from the median of the noise . finally , an auto - detection is made for the motion displacement from the difference image undergone the above pre - processings
本文给出的方法以散射图去除光照影响和静止背景，用噪声的中位数直接估计其方差，从而去除噪声，检测出由运动引起的变动，最后自动检测运动距离。 |
| 7. | The coarse position of moving targets could be obtained by statistically analyzing the difference image that contains motion information , thus the start - up problem of active contour model is solved , and a new color force is constructed according to the image color information
通过对含有运动信息的差分图像进行统计分析，可以获得运动目标的粗略位置，从而解决了主动轮廓的启动问题。 |
| 8. | To solve the first problem , frame difference information is used to direct the location of object regions of difference image frame , and then the objects location information come from d i f ference frame i s used to compound a background frame that does not include any moving object
对背景建模问题，文中提出了根据帧差信息指导不同图像帧中的目标物区域位置定位，据此用不同帧目标物区域像素值合成“空”背景的方法。 |
| 9. | Then the processing methods of inter - frame information in video are presented in detail . the paper discusses video processing technical based on difference . after processing of morphologic operations : image eroding and dilating , we get the binary image to every difference image of video
为了确定图象中人脸的位置，本文引入帧间信息处理技术，采用差分分析方法并利用预处理后差分图象的统计特征，提出一种基于二阶微商算子的人脸定位方法。 |
| 10. | An algorithm for detecting moving ir point target in complex background is proposed , which is based on the reverse phase feature of neighborhood ( rpfn ) of target in difference between neighbor frame images that two positions of the target in the difference image are near and the gray values of them are close to in absolute value but with inverse sign . firstly , pairs of points with rpfn are detected in the difference image between neighbor frame images , with which a virtual vector graph is made , and then the moving point target can be detected by the vectors ' sequence cumulated in vector graphs . in addition , a theorem for the convergence of detection of target contrail by this algorithm is given and proved so as to afford a solid guarantee for practical applications of the algorithm proposed in this paper . finally , some simulation results with 1000 frames from 10 typical images in complex background show that moving point targets with snr not lower than 1 . 5 can be detected effectively
基于运动点目标在邻帧差分图像中所具有的近邻反相特征,即运动点目标的两个位置相邻近、灰度值一正一负,提出一种在复杂背景下,基于红外序列图像的运动点目标检测算法.本算法利用该特征在邻帧差分图像中检测反相点对,进而构造反相点对矢量图,最后依据累积反相点对矢量图中多矢量首位相接的连续性检测出运动的点目标.文中给出并证明应用本算法能以概率1检测到运动点目标的收敛性定理.对典型复杂背景下10幅1000帧图像的仿真结果表明,当信噪比大于或等于1 . 5时,可以有效检测出运动点目标 |
