Color detector for vehicle

Abstract

A color detector for a vehicle that detects a color of an external image by receiving predetermined image data from a camera photographing the external image of the vehicle, may include an RGB converting unit converting a photographed image of the camera into RGB image data, an HSI (Hue, Saturation, and Intensity) image extracting unit extracting a hue image, a saturation image, and an intensity image of the RGB image data, a reverse image extracting unit extracting a reverse saturation image, a reverse modulo saturation image, and a reverse luminance image of the RGB image data, and a color detecting unit detecting white, black, red, and yellow colors by using two or more images selected from the hue image, the saturation image, the intensity image, the reverse saturation image, the reverse modulo saturation image, and the reverse luminance image by a predetermined algorithm.

Description

technical field [0001] The present invention relates to a color detector for a vehicle, and more particularly to such a color detector, which can increase the detection of obstacles on the road where the vehicle is driving by the real-time color information of the image obtained by the color camera installed in the vehicle Rate. Background technique [0002] Typically, obstacle detection systems with radar sensors or ultrasonic sensors are used to detect obstacles on the road for a moving vehicle. [0003] However, since the obstacle detection system with a radar sensor or an ultrasonic sensor is mainly set up to prevent a slight collision between the vehicle and the obstacle, the obstacle detection system does not have the function of judging the type of obstacle or the risk level of the obstacle. [0004] That is, since the type and risk level of an obstacle cannot be recognized using only a distance measuring sensor such as a radar sensor or an ultrasonic sensor, a camer...

AI Technical Summary

Problems solved by technology

[0006] However, as image information for the Lane Departure Warning System (LDWS) and Lane Keeping Support (LKS) systems, black and white images are used, and since black and white images use only edge and brightness information, only limited objects such as lanes can be detected

[0007] That is to say, the LDWS and LKS systems of vehicles generally work with monochrome cameras. However, since monochrome cameras basically cannot use the color information of the image, there are limitations

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