Abstract: A method for monitoring an object is provided. The method includes the steps of: in response to information on a behavior of a domestic animal being estimated from sensor data measured by a sensor for the domestic animal using a machine learning-based behavior recognition model, estimating health status of the domestic animal with reference to the information on the behavior of the domestic animal and a health criterion for the domestic animal; and determining first breeding information on the domestic animal to be provided to a user on the basis of the health status.

Abstract: Provided is an image sensor. The image sensor includes a pixel array including a plurality of pixel blocks. Each of the plurality of pixel blocks includes a plurality of pixels arranged in a matrix form. Each of the plurality of pixels includes a plurality of phase difference sensing pixels. Each of the plurality of phase difference sensing pixels may be periodically repeatedly arranged in the pixel array in a horizontal direction and a vertical direction.

Abstract: The present invention relates to an auto-focus system and method based on a sensor, using hierarchical extraction and motion estimation for an image. The auto-focus method may include the steps of: (a) extracting a phase difference image from a sensed image; (b) extracting a robust feature image which satisfies a preset reference with respect to noise and out-of-focus blur, from the phase difference image; and (C) estimating a motion vector for lens shift from the feature image.

Abstract: Provided is an image sensor. The image sensor includes a pixel array including a plurality of pixel blocks. Each of the plurality of pixel blocks includes a plurality of pixels arranged in a matrix form. Each of the plurality of pixels includes a plurality of phase difference sensing pixels. Each of the plurality of phase difference sensing pixels may be periodically repeatedly arranged in the pixel array in a horizontal direction and a vertical direction.

Abstract: Provided are a non-dyadic lens distortion correction method and an apparatus thereof. The non-dyadic lens distortion correction method includes: (a) acquiring a non-dyadic lens image photographed through a non-dyadic lens; (b) correcting geometric distortion for the non-dyadic lens image by stage by applying a magnification ratio based on a projection model; and (c) compensating a high-frequency component of an image corrected in a previous step by the patch unit in the non-dyadic lens image of which the geometric distortion is corrected.

Abstract: The present invention relates to an auto-focus system and method based on a sensor, using hierarchical extraction and motion estimation for an image. The auto-focus method may include the steps of: (a) extracting a phase difference image from a sensed image; (b) extracting a robust feature image which satisfies a preset reference with respect to noise and out-of-focus blur, from the phase difference image; and (C) estimating a motion vector for lens shift from the feature image.

Abstract: Provided are a non-dyadic lens distortion correction method and an apparatus thereof. The non-dyadic lens distortion correction method includes: (a) acquiring a non-dyadic lens image photographed through a non-dyadic lens; (b) correcting geometric distortion for the non-dyadic lens image by stage by applying a magnification ratio based on a projection model; and (c) compensating a high-frequency component of an image corrected in a previous step by the patch unit in the non-dyadic lens image of which the geometric distortion is corrected.

Abstract: An apparatus and method for image interpolation based on low pass filtering are provided. The apparatus includes an edge direction detector detecting an edge direction for a pixel nearest to a to-be-interpolated pixel among pixels and determining the edge direction of the to-be-interpolated pixel as the detected edge direction, a pixel value calculator calculating pixel values of interpolation points located in a lattice filtering window having a predetermined size by using pixel values of pixels located adjacent to the interpolation points, and a filtering unit performing low pass filtering on the to-be-located pixel according to a low pass filter corresponding to the determined edge direction of the to-be-interpolated pixel, the low pass filter being one of low pass filters corresponding to predetermined vertical, horizontal, left diagonal and right diagonal directions respectively.

Abstract: Methods and apparatus are disclosed for digital image restoration. The method including the steps of receiving an external deteriorated image, and generating N restoration images by using a preset PSF and an image restoration filter without computing a PSF of the input deteriorated image, dividing the restoration images into window parts of a predetermined window size, computing absolute values of differences among peripheral pixels within the divided window parts, selecting only a high frequency part, and analyzing focus deterioration; determining weights of the N restoration images, selecting window parts having high weights, and integrating the selected window parts into one image and comparing a degree of restoration of the integrated image with a preset degree of restoration, and outputting the integrated image as a resultant image when the degree of restoration of the integrated image is higher than the preset degree of restoration.

Abstract: An apparatus and method for image interpolation based on low pass filtering are provided. The apparatus includes an edge direction detector detecting an edge direction for a pixel nearest to a to-be-interpolated pixel among pixels and determining the edge direction of the to-be-interpolated pixel as the detected edge direction, a pixel value calculator calculating pixel values of interpolation points located in a lattice filtering window having a predetermined size by using pixel values of pixels located adjacent to the interpolation points, and a filtering unit performing low pass filtering on the to-be-located pixel according to a low pass filter corresponding to the determined edge direction of the to-be-interpolated pixel, the low pass filter being one of low pass filters corresponding to predetermined vertical, horizontal, left diagonal and right diagonal directions respectively.

Abstract: Disclosed herein are an environmentally-friendly biocomposite prepared from a mixture, as a reinforcement, of algae fibers extracted from algae and a polymeric reagent by means of high-temperature compression-molding, and a method for preparing the biocomposite.

Abstract: An effective H.264/AVC CAVLC decoding method is disclosed. In accordance with the method a VLC code is classified into groups according to a correlation thereof, an arithmetic equation is defined for each of the groups, and a decoding is carried out according to the arithmetic equation in order to minimize a memory access by a table look-up and reduce a decoding time and a power consumption.

Abstract: Methods and apparatus are disclosed for digital image restoration. The method including the steps of receiving an external deteriorated image, and generating N restoration images by using a preset PSF and an image restoration filter without computing a PSF of the input deteriorated image, dividing the restoration images into window parts of a predetermined window size, computing absolute values of differences among peripheral pixels within the divided window parts, selecting only a high frequency part, and analyzing focus deterioration; determining weights of the N restoration images, selecting window parts having high weights, and integrating the selected window parts into one image and comparing a degree of restoration of the integrated image with a preset degree of restoration, and outputting the integrated image as a resultant image when the degree of restoration of the integrated image is higher than the preset degree of restoration.

Abstract: An effective H.264/AVC CAVLC decoding method is disclosed. In accordance with the method a VLC code is classified into groups according to a correlation thereof, an arithmetic equation is defined for each of the groups, and a decoding is carried out according to the arithmetic equation in order to minimize a memory access by a table look-up and reduce a decoding time and a power consumption.