Abstract:
An offline document de-identification apparatus and method, and an offline document restoration apparatus, are disclosed. The offline document de-identification apparatus may include an image obtainer acquiring offline document as an image, a document area detector detecting a document area in the acquired image, a de-identifier performing de-identification on a first area which is an area including the personal information in the document area, and a printer outputting document including the de-identified first area.
Abstract:
The present invention relates to a method of tracking an object in a multiple cameras environment and the method includes generating first feature information of the object from an image input from a first camera; detecting a second camera in which identification information for the object is recognized when the object moves out of a view angle of the first camera, and comparing second feature information of the object generated from an image input from the second camera with the first feature information to track the object from the image input from the second camera. According to the present invention, the object is tracked based on an image in one camera image and if the object moves out of the camera, the identification information of the terminal which is possessed by the object is recognized to hand over the camera to continuously track the same object.
Abstract:
A system for processing a masking region includes a transmitter configured to detect an object region, on which masking is to be performed, from an input image through a camera, convert the detected object region into a block region to perform masking, and encode and transmit an input image on which the masking is completed and a receiver configured to decode an image transmitted from the transmitted to extract a frame therefrom, detect a masked block region by units of extracted frames, and unmask the detected block region to restore the masked image to an original image.
Abstract:
Disclosed is a learning method using extracted data features for simplifying a learning process or improving accuracy of estimation. The learning method includes dividing input learning data into two groups based on a predetermined reference, extracting data features for distinguishing the two divided groups, and performing learning using the extracted data features.