Method and device for detecting road region as well as method and device for detecting road line

• US 8,861,791 B2
• Filed: 12/05/2012
• Issued: 10/14/2014
• Est. Priority Date: 12/22/2011
• Status: Active Grant

• Current Assignee: Ricoh Company Limited
• Original Assignee: Ricoh Company Limited
• Inventors: Zheng, Jichuan, You, Ganmei
• Primary Examiner(s): Fitzpatrick, Atiba O
• Assistant Examiner(s): JAMES, THOMAS AIDEN
• Application Number:
  US13/705,718
• Publication Number:
  US 20130163821A1
• Time in Patent Office: 678 Days
• Field of Search: None
• US Class Current: 382/104
• CPC Class Codes: G01C 11/04 Interpretation of pictures
• CPC Class Codes: G01C 21/28 with correlation of data from several navigational instruments
• CPC Class Codes: G06T 2207/10028 Range image; Depth image; 3D point clouds
• CPC Class Codes: G06T 2207/30256 Lane; Road marking
• CPC Class Codes: G06T 7/13 Edge detection
• CPC Class Codes: G06V 10/443 by matching or filtering
• CPC Class Codes: G06V 20/588 Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road
• CPC Class Codes: G06V 20/647 by matching two-dimensional images to three-dimensional objects

Abstract

Disclosed are a road line detection method and a road line detection device. The road line detection method comprises a step of obtaining a first disparity map including one or more road regions and a corresponding V-disparity image; a step of sequentially detecting plural sloped line segments in the corresponding V-disparity image according to a big-to-small order of disparities and a big-to-small order of V-values, to serve as plural sequentially adjacent road surfaces; a step of obtaining a second disparity map of plural road line regions of interest corresponding to the plural sloped line segments; and a step of detecting one or more road lines in the second disparity map of the plural road line regions of interest.

Claims

1. A road line detection method comprising:

obtaining a first disparity map including one or more road regions and a corresponding V-disparity image, the V-disparity image being a lateral view of the first disparity map;

sequentially detecting plural sequentially adjacent road surfaces by iteratively detecting road surfaces based on corresponding sloped line segments in the V-disparity image from a starting point where disparity and V-value is maximum, each road surface being formed by linear fitting a plurality of reliable points that do not form a vertical line and whose gray levels are greater than a threshold and disparities are less than the reliable points of previously detected road surfaces;

for each of the detected road surfaces, obtaining a second disparity map; and

detecting one or more road lines in the second disparity map.

2. The method according to claim 1, further comprising:

for each of the road lines detected in the second disparity map,

obtaining points in a U-disparity image, corresponding to this road line, the U-disparity image being a top view of the first disparity map;

determining whether the obtained points are located on a non-vertical and non-horizontal sloped line; and

discarding this road line if it is determined that the obtained points are not located on the sloped line.

3. The method according to claim 1, wherein, the detecting a first road surface includes:

finding all of the sloped line segments in the corresponding V-disparity image by utilizing a Hough transform; and

selecting, from all of the sloped lines segments, one sloped line segment on which the number of pass points is maximum or whose disparity is maximum or whose length is maximum, and then letting the selected sloped line segment be the first sloped line.

4. The method according to claim 1, wherein:

the first disparity map is obtained by performing calculation with regard to left and right images of a scene in front of a vehicle; and

the detecting the first road surface includes seeking points satisfying

5. The method according to claim 1, further comprising:

before detecting the plural sloped line segments, removing at least one vertical line, whose length is greater than a predetermined threshold value, in the corresponding V-disparity image.

6. The method according to claim 1, further comprising:

if a V-axis length of any one of the plural road line regions of interest in a second disparity map is greater than a predetermined threshold, then dividing this road line region of interest along its height direction so as to obtain plural new road line regions of interest.

7. The method according to claim 1, further comprising:

if a slope of any one of the detected road lines is not within a predetermined range, then discarding this road line.

10. The method according to claim 1, wherein the gray level of each of the plurality of reliable points forming the corresponding sloped line segment associated with a detected road surface in the second disparity map is set to a same level.

8. A road region detection method comprising:

obtaining a V-disparity image including one or more road regions, the V-disparity image being a lateral view obtained from a first disparity map; and

sequentially detecting plural sequentially adjacent road by iteratively detecting road surfaces based on corresponding sloped line segments in the V-disparity image from a starting point where disparity and V-value is maximum, each road surface being formed by linear fitting a plurality of reliable points that do not form a vertical line and whose gray levels are greater than a threshold and disparities are less than the reliable points of previously detected road surfaces.

9. A road line detection device comprising:

a processor configured to execute program instructions, the program instructions configuring the processor to,

obtain a first disparity map including one or more road regions and a corresponding V-disparity image, the V-disparity image being a lateral view of the first disparity map;

sequentially detect plural sequentially adjacent road surfaces by iteratively detecting road surfaces based on corresponding sloped line segments in the V-disparity image from a starting point where disparity and V-value is maximum, each road surface being formed by linear fitting a plurality of reliable points that do not form a vertical line and whose gray levels are greater than a threshold and disparities are less than the reliable points of previously detected road surfaces;

obtain a second disparity map; and

detect one or more road lines in the second disparity map.

11. The device according to claim 9, wherein the gray level of each of the plurality of reliable points forming the corresponding sloped line segment associated with a detected road surface in the second disparity map is set to a same level.