Samsung Sds Co., Ltd.

Seong Jong Ha

Sang Hak Lee

Jong Hang Kim

Yeon Hee Kwon

Yu Ri Ahn

Bo Youn Kim

Sudhakar Sah

Sun Ah Kang

Young Min Shin

Provided is a machine learning-based object detection method performed by an object detection apparatus. the method comprises constructing an object detection model by performing machine learning on a training image set, wherein the object detection model is a model for detecting a target object in an input image based on the result of comparing a confidence score for the target object with a threshold value, obtaining an input image given a detection result for the target object, wherein the obtained input image is an image not included in the training image set, predicting one or more object regions, in which the target object exists, in the obtained input image by using the object detection model, classifying a region not matching the detection result among the predicted object regions as a false detection region; and adjusting the threshold value of the object detection model based on a confidence score of the false detection region.

Machine learning-based object detection method and apparatus

According to a first aspect of the present invention, a method for setting a region of interest may include: detecting a mark in an image frame photographed by a camera; and setting a region of interest using the detected mark.

Method and apparatus for setting region of interest

According to an aspect of the present invention, there is provided a method of detecting a repetitive pattern. The method includes: clustering a plurality of pixels that form an input image according to color and obtaining one or more color layers composed of pixels included in each cluster; selecting one or more effective layers from the color layers, wherein each of the effective layers includes a predetermined number or more of pixel components, each composed of a plurality of pixels and having a predetermined shape or a predetermined size of area; selecting a unit pattern repeatedly disposed at different locations in each effective layer from the pixel components included in each effective layer; calculating distances between the unit patterns in each effective layer; and calculating a repetition cycle of the unit pattern of the input image based on the calculated distances in each effective layer.

Method and apparatus for detecting repetitive pattern in image

Growing community of inventors

Seoul, South Korea

Seong Jong Ha