Electronics and Telecommunications Research Institute

Kil Taek Lim

Yun Su Chung

Byung Gil Han

Soo In Lee

Eun Chang Choi

Jang Woon Baek

Hyun Woo Kang

Yun Won Choi

Kyu Bo Cho

Pyong Kun Kim

Jong Taek Lee

Kwang Ju Kim

Joon Goo Lee

Provided is a method of creating a local database for local optimization of an object detector based on a deep neural network. The method includes performing preprocessing on an image extracted from real-time collected or pre-collected images from an edge device, modeling a static background image based on the image received through the pre-processing unit and calculating a difference image between a current input image and a background model to model a dynamic foreground image, detecting an object image from the image based on a training model, and creating a local database based on the background image, the foreground image synthesized with the background image, and the object image synthesized with the background image.

System for local optimization of object detector based on deep neural network and method of creating local database therefor

Provided is a technology for recognizing vehicle license plate information which includes detecting a position of a license plate from a vehicle image obtained by imaging a vehicle, extracting individual character images by separating a plurality of characters from a region of the detected license plate in the vehicle image and extracting a license plate type of the license plate according to a predetermined criterion, recognizing a license plate character string on the basis of the extracted individual character images and the license plate type and outputting the recognized license plate character string.

System and method for recognizing vehicle license plate information

A method and apparatus for detecting and recognizing an object using a vector histogram based on a local binary pattern are disclosed. The apparatus of detecting and recognizing an object using a local binary pattern includes: a feature map creator configured to extract an object area in which a moving object exists from an input image, to create a local binary pattern by designating a local area in the object area, and to create a vector component map including information about magnitude vector components and direction vector components using the local binary pattern; a feature map configuring unit configured to divide the object area into a plurality of blocks and to create a feature vector map through a histogram using the vector component map in a unit of the block; and an object detector configured to detect and classify the moving object based on the feature vector map.

Method and apparatus for detecting and recognizing object using local binary patterns

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Daegu, South Korea

Kil Taek Lim