OBSTACLE DETECTION SYSTEM

• US 20130027196A1
• Filed: 07/26/2011
• Published: 01/31/2013
• Est. Priority Date: 07/26/2011
• Status: Active Grant

• Current Assignee: Harman International (China) Holdings Co. Ltd. (Samsung Electronics Co. Ltd.)
• Original Assignee: Harman International Industries Incorporated (Samsung Electronics Co. Ltd.)
• Inventors: Yankun, Zhang, Chuyang, Hong, Weyrich, Norman
• Granted Patent: US 8,611,598 B2
• Time in Patent Office: Days
• US Class Current: 340/435
• CPC Class Codes: G06V 20/58 Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads

Abstract

A computer-implemented method of detecting objects in a path of a vehicle is provided. An image frame that depicts the path of the vehicle is obtained. An edge-image corresponding to the image frame is generated. A binary image corresponding to the edge-image is also generated. One or more blobs in the binary image that respectively correspond to one or more objects in the image frame are identified. Based on an analysis of the blobs in the binary image, a determination is made that one of the objects in the image frame is an obstacle in the path of the vehicle.

Claims

1. A computer-implemented method of detecting objects in a path of a vehicle comprising:

obtaining an image frame that depicts the path of the vehicle;

generating an edge-image corresponding to the image frame;

generating a binary image corresponding to the edge-image;

identifying one or more blobs in the binary image that respectively correspond to one or more objects in the image frame; and

determining that one of the objects in the image frame is an obstacle in the path of the vehicle based on an analysis of the blobs in the binary image.

2. The computer-implemented method of claim 1 further comprising generating a warning signal in response to the determination that the obstacle is in the path of the vehicle such that receipt of the warning signal at an output device causes the output device to output an alarm.

3. The computer-implemented method of claim 1 where the image frame is a color image frame and further comprising generating a grayscale image frame corresponding to the color image frame.

4. The computer-implemented method of claim 1 further comprising performing a multi-scale integral image-based segmentation of the image frame to generate the edge-image.

5. The computer-implemented method of claim 4 where the edge-image comprises a grid of pixels, individual pixels having a pixel value and further comprising comparing the pixel value of the individual pixels in the edge-image to a predetermined pixel value threshold to generate the binary image.

6. The computer-implemented method of claim 5 further comprising:

performing an erosion morphological operation on the binary image to shrink at least one of the blobs in the binary image; and

performing a dilation morphological operation on the binary image to expand at least one of the blobs in the binary image.

7. The computer-implemented method of claim 6 further comprising performing a labeling operation on the binary image to identify one or more components in the binary image such that each component includes one or more of the blobs in the binary image and each component respectively corresponds to one of the objects in the image frame.

8. The computer-implemented method of claim 7 where the binary image comprises a grid of pixels and each component in the binary image has a total pixel area, the method further comprising:

comparing the total pixel area of each component in the binary image to a predetermined pixel area threshold; and

in response to a determination that a component has a total pixel area smaller than the predetermined pixel area threshold, removing the blobs of the component from the binary image.

9. The computer-implemented method of claim 8 further comprising:

determining an ellipse for one of the components in the binary image such that the size of the ellipse corresponds to the total pixel area of the component;

generating a top-view image corresponding to the image frame;

prolongating an axis of the ellipse towards a focus of the top-view image to obtain a prolongation for the ellipse;

determining that the prolongation passes through a predetermined area around the focus; and

in response to a determination that the prolongation passes through the predetermined area, determining that the object in the image frame corresponding to the component for the ellipse is an obstacle in the path of the vehicle.

10. The computer-implemented method of claim 1 further comprising adjusting the image frame to correct for lens distortion in the image frame.

20. The system of claim 10 further comprising a distortion correction module that adjusts the image frame to correct for lens distortion in the image frame.

11. A system for detecting objects in a path of a vehicle comprising:

an image segmentation module that generates an edge-image corresponding to an image frame, the image frame depicts the path of the vehicle;

a binary image creation module that generates a binary image corresponding to the edge-image;

a blob analysis module that identifies one or more blobs in the binary image that respectively correspond to one or more objects in the image frame; and

an obstacle verification module that determines one of the objects in the image frame is an obstacle in the path of the vehicle based on an analysis of the blobs in the binary image.

12. The system of claim 11 where the system generates a warning signal in response to the determination that the obstacle is in the path of the vehicle such that receipt of the warning signal at an output device causes the output device to output an alarm.

13. The system of claim 11 where the image frame is a color image frame and further comprising a grayscale transformation module that generates a grayscale image frame corresponding to the color image frame.

14. The system of claim 11 where the image segmentation module performs a multi-scale integral image-based segmentation of the image frame to generate the edge-image.

15. The system of claim 14 where:

the edge-image comprises a grid of pixels, individual pixels having a pixel value; and

the binary image creation module compares the pixel value of the individual pixels in the edge-image to a predetermined pixel value threshold to generate the binary image.

16. The system of claim 15 further comprising a blob analysis module that performs an erosion morphological operation on the binary image to shrink at least one of the blobs in the binary image and performs a dilation morphological operation on the binary image to expand at least one of the blobs in the binary image.

17. The system of claim 16 where the blob analysis module performs a labeling operation on the binary image to identify one or more components in the binary image such that each component includes one or more of the blobs in the binary image and each component respectively corresponds to one of the objects in the image frame.

18. The system of claim 17 where:

the binary image comprises a grid of pixels;

each component in the binary image has a total pixel area;

the blob analysis module compares the total pixel area of each component in the binary image to a predetermined pixel area threshold; and

in response to a determination that one of the components has a total pixel area smaller than the predetermined pixel area threshold, the blob analysis module removes the blobs of the component from the binary image.

19. The system of claim 18 where:

the blob analysis module determines an ellipse for one of the components in the binary image such that the size of the ellipse corresponds to the total pixel area of the component;

the obstacle verification module generates a top-view image corresponding to the image frame;

the obstacle verification module prolongates an axis of the ellipse towards a focus of the top-view image to obtain a prolongation for the ellipse;

the obstacle verification module determines that the prolongation passes through a predetermined area around the focus; and

in response to a determination that the prolongation passes through the predetermined area, determining that the object in the image frame corresponding to the component for the ellipse is an obstacle in the path of the vehicle.