Abstract: A data clustering method, a data clustering device using the same, and an image processing apparatus and a data processing apparatus equipped with the data clustering device are provided. The method includes sorting a plurality of data point to be clustered and generating a processing sequence based on the sorting, wherein each of the data point has at least one feature value. The method also includes using a non-iterative mechanism to cluster the data points into a plurality of data clusters according to the processing sequence. The method further includes optimizing the generated data clusters. Accordingly, the data clustering method can fast cluster the data points.

Abstract: A cascadable camera tampering detection transceiver module has a processing unit and a storing unit, an information controlling module and an analyzing module. The storing unit stores a transceiving module. The detection module analyzes input video, detects camera tampering events, synthesizes the input video with the image of camera tampering result, and outputs the synthesized video. When the input video is an output from the detection module, the detection module separates the camera tampering result from the input video, and the result can be used to simplify or enhance the subsequent video analysis. Performing the existing analysis repeatedly may be avoided, and the user may re-define the detection conditions in this manner. When the camera tampering result is transmitted in the video channel, the detection module transmits the camera tampering result, and hence the detection module may be used in combination with surveillance devices having image output or input interfaces.

Abstract: An apparatus and a method for fast foreground detection are provided. A foreground characteristic value calculation module calculates a foreground characteristic value by using an image intensity of each pixel in a target image and a background intensity of a corresponding pixel in a background model. A first filter determines a first threshold and a second threshold according to at least one scenic factor for capturing the target image and filters out non-foreground pixels having their foreground characteristic value between the first threshold and the second threshold from pixels in the target image. A second filter determines an image difference condition and a chroma similarity condition according to the scenic factor and filters out non-foreground pixels having their foreground characteristic value satisfying the image difference condition and the chroma similarity condition from pixels left by the first filter. Pixels left by the second filter are served as foreground pixels.

Abstract: A light information receiving method, a method and a unit for the recognition of light-emitting objects are provided. The light information receiving method includes the following steps. A light-emitting object array is captured to obtain a plurality of images, wherein the light-emitting object array includes at least one light-emitting object. A temporal filtering process is performed to the images to recognize a light-emitting object. A light-emitting status of the light-emitting object array is recognized according to the light-emitting object location. A decoding process is performed according to the light-emitting status to output an item of information.

Abstract: An apparatus and a method for fast foreground detection are provided. A foreground characteristic value calculation module calculates a foreground characteristic value by using an image intensity of each pixel in a target image and a background intensity of a corresponding pixel in a background model. A first filter determines a first threshold and a second threshold according to at least one scenic factor for capturing the target image and filters out non-foreground pixels having their foreground characteristic value between the first threshold and the second threshold from pixels in the target image. A second filter determines an image difference condition and a chroma similarity condition according to the scenic factor and filters out non-foreground pixels having their foreground characteristic value satisfying the image difference condition and the chroma similarity condition from pixels left by the first filter. Pixels left by the second filter are served as foreground pixels.

Abstract: Methods and systems are disclosed for processing compressed video images. A processor detects a candidate object region from the compressed video images. The candidate object region includes a moving object and a shadow associated with the moving object. For each data block in the candidate object region, the processor calculates an amount of encoding data used to encode temporal changes in the respective data block. The processor then identifies the shadow in the candidate object region composed of data blocks each having the amount of encoding data below a threshold value.

Abstract: A cascadable camera tampering detection transceiver module has a processing unit and a storing unit, an information controlling module and an analyzing module. The storing unit stores a transceiving module. The detection module analyzes input video, detects camera tampering events, synthesizes the input video with the image of camera tampering result, and outputs the synthesized video. When the input video is an output from the detection module, the detection module separates the camera tampering result from the input video, and the result can be used to simplify or enhance the subsequent video analysis. Performing the existing analysis repeatedly may be avoided, and the user may re-define the detection conditions in this manner. When the camera tampering result is transmitted in the video channel, the detection module transmits the camera tampering result, and hence the detection module may be used in combination with surveillance devices having image output or input interfaces.

Abstract: A data clustering method, a data clustering device using the same, and an image processing apparatus and a data processing apparatus equipped with the data clustering device are provided. The method includes sorting a plurality of data point to be clustered and generating a processing sequence based on the sorting, wherein each of the data point has at least one feature value. The method also includes using a non-iterative mechanism to cluster the data points into a plurality of data clusters according to the processing sequence. The method further includes optimizing the generated data clusters. Accordingly, the data clustering method can fast cluster the data points.

Abstract: An apparatus for a video object detection algorithm of a camera includes a video object detection training module and a video object detection application module. The video object detection training module is configured to generate an optimum correspondence between quantified values of environmental variables and parameters of a video object detection algorithm according to a stream of training video signals and a video object detection reference result. The video object detection application module is configured to perform video object detection on a stream of training video signals based on the optimum correspondence between the quantified values of the environmental variables and the parameters of the video object detection algorithm.

Abstract: A camera calibration system including a coordinate data generation device and a coordinate data recognition device is provided. The coordinate data generation device generates a plurality of map coordinate data corresponding to a plurality of real positions in a real scene. The coordinate data recognition device receives an image plane of the real scene from a camera to be calibrated and receives the map coordinate data from the coordinate data generation device. Besides, the coordinate data recognition device recognizes image positions corresponding to the real positions in the image plane and calculates image coordinate data corresponding to the image positions. Moreover, the coordinate data recognition device calculates a coordinate transform matrix corresponding to the camera according to the image coordinate data and the map coordinate data. Thereby, the camera calibration system can finish the calibration of the camera quickly.

Abstract: A light information receiving method, a method and a unit for the recognition of light-emitting objects are provided. The light information receiving method includes the following steps. A light-emitting object array is captured to obtain a plurality of images, wherein the light-emitting object array includes at least one light-emitting object. A temporal filtering process is performed to the images to recognize a light-emitting object. A light-emitting status of the light-emitting object array is recognized according to the light-emitting object location. A decoding process is performed according to the light-emitting status to output an item of information.