Industrial Technology Research Institute

Sheng-Wei Chan

Che-Tsung Lin

Yu-Chung Chen

Pin-Yung Chen

Daniel Alberto Reyes Uquillas

Chantel Lin

Yan-Yu Lin

Chen-Hui Hu

Chiao-Tung Chan

The present disclosure provides a camera calibration method based on vehicle localization, mainly considering that a vehicle is not of an ideal rigid structure, and shaking of a vehicle body during operation, uneven road surfaces, or different loads will cause variations in extrinsic parameters of a camera system, resulting in perceptual information errors. Therefore, through perceptual information from a fused image, an inertial measurement unit, a speedometer, and the like, combined with the road and marking information provided by a high-definition map, the relative motion between the vehicle body and a vehicle chassis is simultaneously described with a mass-spring-damper model, so as to complete the determination of six-degree-of-freedom positions of the vehicle body and the vehicle chassis, and finally the extrinsic parameters of cameras are immediately calibrated with the vehicle chassis as reference coordinates.

Camera calibration method based on vehicle localization

A traffic light recognition system including a map, a localization module, at least one image capturing device and an image processing module is provided. The map is configured to provide an information relevant to a traffic light. The localization module is configured to provide a positioning information relevant to the traffic light. At least one image capturing device is configured to capture a real-time road image relevant to the traffic light. The image processing module is configured to combine the map and the positioning information of the traffic light provided by the localization module to generate a region of interest in the real-time road image captured by the image capturing device, and to recognize the traffic light in the region of interest, wherein the traffic light includes a light box and at least one light signal.

Traffic light recognition system and method thereof

A marked parking space identification system and a marked parking space identification method are disclosed. The marked parking space identification method includes: receiving a first image of a first parking space with markings; identifying a plurality of corners in the first image of the first parking space with markings; pairing up two adjacent corners to become a parking corner group; and using the parking corner group to identify a first marked parking space.

Marked parking space identification system and method thereof

An image processing method is adapted to process images captured by at least two cameras in an image system. In an embodiment, the image processing method comprises: matching two corresponding feature points for two images, respectively, to become a feature point set; selecting at least five most suitable feature point sets, by using an iterative algorithm; calculating a most suitable radial distortion homography between the two images, according to the at least five most suitable feature point sets; and fusing the images captured by the at least two cameras at each of timing sequences, by using the most suitable radial distortion homography.

Image processing method and image system for transportation

An image inpainting method includes the following steps: segmenting image, acquiring a plurality of images, and having the plurality of images segment into noise-contained pixel images and non-noise-contained pixel images, and confirming the positions of every noise pixel of the noise pixel image; and performing inpainting in light of the noise-contained pixel images, finding out the offset map and geometric relationship of the pixel corresponding relationship without being subjected to the affection of noise and having the pixel corresponding relationship with minimum parallax, making use of the offset map or the geometric relationship to extract corresponding pixel that is not subjected to the affection of noise, performing inpainting and substituting the noise pixel in the plurality of images to generate at least a synthetic image without containing noise.

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Taipei, Taiwan

Sheng-Wei Chan