Vehicle detecting method, nighttime vehicle detecting method based on dynamic light intensity and system thereof
First Claim
1. A nighttime vehicle detecting method based on dynamic light intensity, comprising:
- providing a highlight detecting step, wherein the highlight detecting step is for capturing an image by a camera and driving a computing unit to compute the image and then detect a highlight point of the image, the highlight point comprises a plurality of highlight pixels, and the camera and the computing unit are disposed on a driving vehicle;
providing a vehicle lamp judging step, wherein the vehicle lamp judging step is for driving the computing unit to perform a communicating region labeling algorithm to label the highlight pixels connected to each other as a communicating region value, and then performing an area filtering algorithm to analyze an area of the highlight pixels connected to each other and judge whether the highlight pixels connected to each other are a vehicle lamp or not according to a size of the area;
providing an optical flow filtering step, wherein the optical flow filtering step is for driving the computing unit to perform an optical flow algorithm to obtain a speed of the vehicle lamp, and then filtering the vehicle lamp moved at the speed smaller than a predetermined speed; and
providing a distance estimating step, wherein the distance estimating step is for driving the computing unit to perform a coordinate conversion algorithm to estimate a distance between the vehicle lamp and the camera;
wherein the highlight detecting step comprises;
providing a histogram equalization step, wherein the histogram equalization step is for counting a number of occurrences of each of a plurality of gray scale values of the image, and changing the gray scale values to generate a plurality of equalized gray scale values according to the number of occurrences.
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Abstract
A nighttime vehicle detecting method is for capturing an image by a camera and driving a computing unit to compute the image and then detect a highlight point of the image. The nighttime vehicle detecting method is for driving the computing unit to perform a communicating region labeling algorithm to label a plurality of highlight pixels connected to each other as a communicating region value, and then performing an area filtering algorithm to analyze an area of the highlight pixels connected to each other and judge whether the highlight pixels connected to each other are a vehicle lamp or not according to a size of the area. The nighttime vehicle detecting method is for driving the computing unit to perform an optical flow algorithm to obtain a speed of the vehicle lamp, and then filtering the vehicle lamp moved at the speed smaller than a predetermined speed.
3 Citations
19 Claims
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1. A nighttime vehicle detecting method based on dynamic light intensity, comprising:
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providing a highlight detecting step, wherein the highlight detecting step is for capturing an image by a camera and driving a computing unit to compute the image and then detect a highlight point of the image, the highlight point comprises a plurality of highlight pixels, and the camera and the computing unit are disposed on a driving vehicle; providing a vehicle lamp judging step, wherein the vehicle lamp judging step is for driving the computing unit to perform a communicating region labeling algorithm to label the highlight pixels connected to each other as a communicating region value, and then performing an area filtering algorithm to analyze an area of the highlight pixels connected to each other and judge whether the highlight pixels connected to each other are a vehicle lamp or not according to a size of the area; providing an optical flow filtering step, wherein the optical flow filtering step is for driving the computing unit to perform an optical flow algorithm to obtain a speed of the vehicle lamp, and then filtering the vehicle lamp moved at the speed smaller than a predetermined speed; and providing a distance estimating step, wherein the distance estimating step is for driving the computing unit to perform a coordinate conversion algorithm to estimate a distance between the vehicle lamp and the camera; wherein the highlight detecting step comprises; providing a histogram equalization step, wherein the histogram equalization step is for counting a number of occurrences of each of a plurality of gray scale values of the image, and changing the gray scale values to generate a plurality of equalized gray scale values according to the number of occurrences. - View Dependent Claims (2, 3, 4, 5, 6)
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7. A nighttime vehicle detecting system based on dynamic light intensity, comprising:
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a camera disposed on a driving vehicle and configured to capture an image; and a computing unit disposed on the driving vehicle and comprising; a highlight detecting module signally connected to the camera, wherein the highlight detecting module is configured to compute the image and then detect a highlight point of the image, and the highlight point comprises a plurality of highlight pixels; a vehicle lamp judging module signally connected to the highlight detecting module, wherein the vehicle lamp judging module is configured to perform a communicating region labeling algorithm to label the highlight pixels connected to each other as a communicating region value, and then perform an area filtering algorithm to analyze an area of the highlight pixels connected to each other and judge whether the highlight pixels connected to each other are a vehicle lamp or not according to a size of the area; an optical flow filtering module signally connected to the vehicle lamp judging module, wherein the optical flow filtering module is configured to perform an optical flow algorithm to obtain a speed of the vehicle lamp, and then filter the vehicle lamp moved at the speed smaller than a predetermined speed; and a distance estimating module signally connected to the optical flow filtering module, wherein the distance estimating module is configured to perform a coordinate conversion algorithm to estimate a distance between the vehicle lamp and the camera; wherein the highlight detecting module is configured to count a number of occurrences of each of a plurality of gray scale values of the image, and change the gray scale values to generate a plurality of equalized gray scale values according to the number of occurrences. - View Dependent Claims (8, 9, 10, 11, 12)
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13. A vehicle detecting method for detecting a front vehicle of an image, the vehicle detecting method comprising:
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providing an image analyzing step, wherein the image analyzing step is for capturing an image by a camera and driving a computing unit to analyze a sky brightness value of a sky region of the image and compare a predetermined brightness value with the sky brightness value to judge whether the image is in a daytime or a nighttime, and the camera and the computing unit are disposed on a driving vehicle; and providing a vehicle detecting step, wherein the vehicle detecting step is for driving the computing unit to perform a daytime vehicle detecting step or a nighttime vehicle detecting step, when the image is in the daytime, the daytime vehicle detecting step is performed, and when the image is in the nighttime, the nighttime vehicle detecting step is performed; wherein the daytime vehicle detecting step is for detecting a distance between the front vehicle and the camera according to a forward collision warning algorithm; wherein the nighttime vehicle detecting step comprises; providing a highlight detecting step, wherein the highlight detecting step is for driving the computing unit to compute the image and then detect a highlight point of the image, and the highlight point comprises a plurality of highlight pixels; providing a vehicle lamp judging step, wherein the vehicle lamp judging step is for driving the computing unit to perform a communicating region labeling algorithm to label the highlight pixels connected to each other as a communicating region value, and then performing an area filtering algorithm to analyze an area of the highlight pixels connected to each other and judge whether the highlight pixels connected to each other are a vehicle lamp or not according to a size of the area; providing an optical flow filtering step, wherein the optical flow filtering step is for driving the computing unit to perform an optical flow algorithm to obtain a speed of the vehicle lamp, and then filtering the vehicle lamp moved at the speed smaller than a predetermined speed; and providing a distance estimating step, wherein the distance estimating step is for driving the computing unit to perform a coordinate conversion algorithm to estimate a distance between the vehicle lamp and the camera; wherein the highlight detecting step comprises; providing a histogram equalization step, wherein the histogram equalization step is for counting a number of occurrences of each of a plurality of gray scale values of the image, and changing the gray scale values to generate a plurality of equalized gray scale values according to the number of occurrences. - View Dependent Claims (14, 15, 16, 17, 18, 19)
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Specification