Abstract: A video indexing system analyzes contents of source video and develops a visual table of contents using selected images. A system for detecting significant scenes detects video cuts from one scene to another, and static scenes based on DCT coefficients and macroblocks. A keyframe filtering process filters out less desired frames including, for example, unicolor frames, or those frames having a same object as a primary focus or one primary focuses. Commercials may also be detected and frames of commercials eliminated. The significant scenes and static scenes are detected based on a threshold which is set based on the category of the video.

Abstract: An image processing device and method for classifying symbols relies on a connected-component technique for isolating symbol regions. The device and method form connected components from an image derived by the application of an edge detection filter. The formation of connected components from this filtered image defines the edges of character shapes. As a result, the number of pixels that must be connected to define each connected component is substantially reduced and the speed of processing thereby increased. The application of the method is discussed primarily with respect to text in a video stream.

Abstract: A video indexing system analyzes contents of source video and develops a visual table of contents using selected images. A system for detecting significant scenes detects video cuts from one scene to another, and static scenes based on DCT coefficients and macroblocks. A keyframe filtering process filters out less desired frames including, for example, unicolor frames, or those frames having a same object as a primary focus or one primary focuses. Commercials may also be detected and frames of commercials eliminated. The significant scenes and static scenes are detected based on a threshold which is set based on the category of the video.

Abstract: A video indexing system analyzes contents of source video and develops a visual table of contents using selected images. A system for detecting significant scenes detects video cuts from one scene to another, and static scenes based on DCT coefficients and macroblocks. A keyframe filtering process filters out less desired frames including, for example, unicolor frames, or those frames having a same object as a primary focus or one primary focuses. Commercials may also be detected and frames of commercials eliminated. The significant scenes and static scenes are detected based on a threshold which is set based on the category of the video.