Abstract: A multi-function control illumination device has a synchronization separator, a parameter setting device, a light emitting device, and a video processor. The synchronization separator connects with a video camera and the parameter setting device connecting with the light emitting device. The synchronization separator receives a video signal from the video camera, retrieves a synchronization signal from the video signal, and outputs the synchronization signal to the parameter setting device. The parameter setting device generates an electric signal corresponding to the synchronization signal according to at least one illumination parameter and outputs the electric signal to the light emitting device. The light emitting device emits toward a shooting direction of the video camera a light beam whose intensity periodically varies according to the electric signal.

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 image processing method and a system are provided. The image processing method of moving camera comprises the following steps. An image of a road is captured by a first camera unit. A coordinate of the image of an object shown in the image of the road is captured when the image of the object shown in the image of the road is selected. At least an aiming angle of a second camera unit is adjusted according to the coordinate to make the field-of-view of the second camera unit aligned with the object. The image of the object is captured by the second camera unit. The image of the object is enlarged.

Abstract: An efficient 3D object localization method using multiple cameras is provided. The proposed method comprises a three-dimensional object localization process that firstly generates a plurality of two-dimensional line samples originated from a pre-calibrated vanishing point in each camera view for representing foreground video objects, secondly constructs a plurality of three-dimensional line samples from the two-dimensional line samples in all the multiple camera views, and thirdly determines three-dimensional object to locations by clustering the three-dimensional line samples into object groups.

Abstract: The present invention provides a lighting control module, a video camera comprising the same and a control method of the same. The video camera of the invention includes a sensing module, a light-emitting module and a control module. The sensing module receives a reflected light beam from a recording direction of the video camera, and generates an image of a scene in the recording direction. The light-emitting module emits a light toward the recording direction. Additionally, the lighting control module is connected to the light-emitting module for controlling the light-emitting module to periodically emit the light from a first brightness to a second brightness.

Abstract: The present invention provides a lighting control module, a video camera comprising the same and a control method of the same. The video camera of the invention includes a sensing module, a light-emitting module and a control module. The sensing module receives a reflected light beam from a recording direction of the video camera, and generates an image of a scene in the recording direction. The light-emitting module emits a light toward the recording direction. Additionally, the lighting control module is connected to the light-emitting module for controlling the light-emitting module to periodically emit the light from a first brightness to a second brightness.

Abstract: If an active smart node detects that an object leaves a center region of a FOV for a boundary region, the active smart node predicts a possible path of the object. When the object gets out of the FOV, the active smart node predicts the object appears in a FOV of another smart node according to the possible path and a spatial relation between cameras. The active smart node notifies another smart node to become a semi-active smart node which determines an image characteristic similarity between the object and a new object and returns to the active smart node if a condition is satisfied. The active smart node compares the returned characteristic similarity, an object discovery time at the semi-active smart node, and a distance between the active smart node and the semi-active smart node to calculate possibility.

Abstract: An image processing device includes an image acquisition module, a memory module, and an image signal processing module, for performing an image enlargement and enhancement. The image acquisition module sequentially reads in an image block, including a unit pixel matrix and an exterior pixel matrix, wherein each pixel matrix includes a plurality of pixels and each pixel is associated with a parameter. The memory module stores a plurality of predefined edge patterns. The image signal processing module compares a loaded image block with predefined edge patterns, and determines if it is an edge block. Then, the image signal processing module further classifies its pixels into two groups, and calculates a continuous separating boundary between the two groups. Finally, the image signal processing module enlarges an edge block by placing new pixels inside its unit pixel matrix, wherein the new pixel parameters are extrapolated from the two classified pixel groups to maintain a sharp edge boundary.

Abstract: An image processing method and a system are provided. The image processing method of moving camera comprises the following steps. An image of a road is captured by a first camera unit. A coordinate of the image of an object shown in the image of the road is captured when the image of the object shown in the image of the road is selected. At least an aiming angle of a second camera unit is adjusted according to the coordinate to make the field-of-view of the second camera unit aligned with the object. The image of the object is captured by the second camera unit. The image of the object is enlarged.

Abstract: The present invention provides a lighting control module, a video camera comprising the same and a control method of the same. The video camera of the invention includes a sensing module, a light-emitting module and a control module. The sensing module receives a reflected light beam from a recording direction of the video camera, and generates an image of a scene in the recording direction. The light-emitting module emits a light toward the recording direction. Additionally, the lighting control module is connected to the light-emitting module for controlling the light-emitting module to periodically emit the light from a first brightness to a second brightness.

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: Consistent with the disclosed embodiments, the shapes of the windows of vehicles are used as features for recognizing vehicle types. This method transforms vehicle images with different view angles in a homographic manner to a normalized coordinate system and further extracts normalized window images. Subsequently, the method recognizes target vehicle types correctly in accordance with the normalized window images.

Abstract: If an active smart node detects that an object leaves a center region of a FOV for a boundary region, the active smart node predicts a possible path of the object. When the object gets out of the FOV, the active smart node predicts the object appears in a FOV of another smart node according to the possible path and a spatial relation between cameras. The active smart node notifies another smart node to become a semi-active smart node which determines an image characteristic similarity between the object and a new object and returns to the active smart node if a condition is satisfied. The active smart node compares the returned characteristic similarity, an object discovery time at the semi-active smart node, and a distance between the active smart node and the semi-active smart node to calculate possibility.

Abstract: An image processing device includes an image acquisition module, a memory module, and an image signal processing module, for performing an image enlargement and enhancement. The image acquisition module sequentially reads in an image block, including a unit pixel matrix and an exterior pixel matrix, wherein each pixel matrix includes a plurality of pixels and each pixel is associated with a parameter. The memory module stores a plurality of predefined edge patterns. The image signal processing module compares a loaded image block with predefined edge patterns, and determines if it is an edge block. Then, the image signal processing module further classifies its pixels into two groups, and calculates a continuous separating boundary between the two groups. Finally, the image signal processing module enlarges an edge block by placing new pixels inside its unit pixel matrix, wherein the new pixel parameters are extrapolated from the two classified pixel groups to maintain a sharp edge boundary.