Automotive Research & Test Center

Automotive Research & Testing Center

Chih-Hung Yang

Li-You Hsu

Kuo-Ching Chang

Yu-Sheng Liao

A self-adaptive image edge correction device and method thereof, including an image fetching unit, an image processing unit, and an image output unit. Wherein, the image fetching unit is used to provide an original image, and is connected electrically to the image processing unit, that includes a sharpening filter, a superimposer, and an edge detector. The sharpening filter converts the original image into a sharpened edge image, and the superimposer superimposes the original image to the sharpened edge image, to form an enhanced image. The edge detector fetches the edge of the enhanced image, to obtain a differential edge image. The image processing unit then utilizes selectively the horizontal correction or vertical correction to correct the differential edge image, based on s deviation direction of the differential edge image, to form a corrected image, and provide it to the image output unit to output as required.

Self-adaptive image edge correction device and method thereof

An object detection method with a rising classifier effect is embedded in an object detection device and has steps of acquiring image information; determining a position of an obstacle in the image information, wherein the image information is detected for generation of an extracted range corresponding to the obstacle; recognizing an extracted contour of the obstacle, wherein the extracted contour of the obstacle associated with the extracted range is obtained by using an algorithm for Poisson gradient vector flow based active deformable contour model and a multi-mesh algorithm with different grid sizes; and forming a maximum border of the extracted contour of the obstacle for a classifier to recognize a type of the obstacle according to the maximum border of the obstacle. Accordingly, the object detection method is advantageous in complete extraction, higher recognition rate, faster computation and feasibility to be integrated with vehicle systems.

Object detection method with a rising classifier effect and object detection device with the same

A self-adaptive image-based obstacle detection method comprises steps: capturing an original image; transforming the original image to an HSV color space, and retrieving a hue component (H) and a saturation component (S) of the HSV color space to form an HS-based image; dividing the HS-based image into image blocks; selecting one image block as a background block; using an obstacle recognition equation to determine whether each of the image blocks is similar to the background block; if no, deleting the image block; if yes, preserving the image block to form a binary obstacle image; and overlaying the binary obstacle image on the original image to filter out the background and obtain an initial ambit of an obstacle image. Then, three orderly movement flow equations are used to determine whether it is an obstacle.

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Changhua County, Taiwan

Chih-Hung Yang