Abstract: A method for determining a foreground image and a background image, the method includes the following steps, generating a characteristic data of each of N sub-region images of in an interested region of N parent images, classifying the N sub-region images to image groups of in M image groups according to the characteristic data of each of the N sub-region images, obtaining a motion level of each of the M image groups according to a motion area of in the N sub-region images, determining whether each the image group belongs to a background image group or a foreground image group according to each the motion level of each the image group and an image quantity of in each the image group. The method can correctly determine a foreground image and a background image, even a foreground object stops moving and stays in a viewable range of an image apparatus.

Abstract: A method for determining a foreground image and a background image, the method includes the following steps, generating a characteristic data of each of N sub-region images of in an interested region of N parent images, classifying the N sub-region images to image groups of in M image groups according to the characteristic data of each of the N sub-region images, obtaining a motion level of each of the M image groups according to a motion area of in the N sub-region images, determining whether each the image group belongs to a background image group or a foreground image group according to each the motion level of each the image group and an image quantity of in each the image group. The method can correctly determine a foreground image and a background image, even a foreground object stops moving and stays in a viewable range of an image apparatus.

Abstract: An object detection method is disclosed. The method comprises receiving a current frame of a plurality of frames of a video; simultaneously tracking and detecting the current frame to determine an object list; and updating the object list for tracking at least an object of a following frame of the current frame.

Abstract: A motion detection method includes an extracting circuit generating a first representative data according to a first image in an image signal outputted by an image sensor, a buffering circuit storing the first representative data, the extracting circuit generating a second representative data according to a second image in the image signal, the buffering circuit storing the second representative data and outputting the first representative data to a comparing circuit, and the comparing circuit comparing the first representative data and the second representative data, to generate a motion detection result. When the motion detection result represents “motion”, an image-signal-processing circuit of an image signal processor enters active state to generate output signal. By means of the motion detection method, in an imaging device, the image-signal-processing circuit of the image signal processor can switch between active state and power-off/power-saving state even when there is no additional infrared sensor.

Abstract: A method of noise reduction is discloses. The method comprises identifying a plurality of candidate matching blocks in a reference frame for a current patch; obtaining at least one filtering result based on the plurality of candidate matching blocks; determining at least one reference block from a plurality of candidate motion vectors; and generating a de-noised patch for the current patch according to the at least one filtering result and the at least one reference block.