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METHOD FOR REAL-TIME SEGMENTATION OF VIDEO OBJECTS IN KNOWN STATIONARY IMAGE BACKGROUND

机译:已知静止图像背景中视频对象的实时分割方法

摘要

The methods for the segmentation of foreground objects of video images have been developed further since establishment of the conventional color keying methods that required an image background that was colored in a certain manner. Presently used methods are also limited. The program Pfinder for example requires certain information with respect to the form and texture of the foreground object. For the approach of M. Bichsel it is necessary to mark individual background zones. The inventive method facilitates the segmentation of objects of any shape or texture and with any number of holes as long as the color values of the foreground and the background are not identical in a certain image element. For a segmentation of foreground objects the difference between the image to be analyzed and the background image calculated by the average value of several takes of the individual image pixels is compared with a threshold value that is fixed to the maximum noise. Changes of brightness in the background of the image are compensated by adaptation and the adaptation is linked with the segmentation in such a manner that the method works precisely and stably. If several color channels are evaluated, only matching results are used for further analysis.
机译:自从建立需要以某种方式着色的图像背景的常规颜色键控方法以来,已经进一步开发了用于视频图像的前景对象的分割的方法。当前使用的方法也受到限制。程序Pfinder例如需要有关前景对象的形式和纹理的某些信息。对于M. Bichsel的方法,必须标记各个背景区域。本发明的方法有助于分割任何形状或纹理并且具有任何数量的孔的对象,只要前景和背景的颜色值在特定图像元素中不同即可。对于前景物体的分割,将要分析的图像与通过各个图像像素的几次拍摄的平均值计算出的背景图像之间的差异与固定为最大噪声的阈值进行比较。图像背景中亮度的变化通过自适应补偿,并且自适应与分割相关联,从而使该方法精确而稳定地工作。如果评估了多个颜色通道,则仅将匹配结果用于进一步分析。

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