VEHICLE DETECTION METHOD BASED ON THERMAL IMAGING
First Claim
1. A vehicle detection method based on thermal imaging, adapted to capture a total thermal image of a specific region, the vehicle detection method comprising:
- an initial vehicle likelihood region identifying step in which a signature cutting algorithm discerns an initial vehicle likelihood regions and a background region in the total thermal image and deducts the background region by a background deduction technique to identify the initial vehicle likelihood region;
a vehicle window locating step in which a border detection algorithm and a Hough transform detect an object component which has a feature that a pair of parallel horizontal lines are shown in a thermal image of the initial vehicle likelihood regions and a feature that a center of the thermal image is of low brightness, and the object component is regarded as a located vehicle window;
a vehicle bottom locating step in which the border detection algorithm and the Hough transform detect an object component which has a feature that a thermal image of the initial vehicle likelihood regions is slender and a feature that the thermal image is of high brightness, and the object component is regarded as a located vehicle bottom; and
a vehicle detecting step in which a space geometric relationship of the located vehicle window and vehicle bottom is described with a Markov random field, wherein, if the space geometric relationship conforms with a predetermined space geometric relationship, a region having the vehicle window and vehicle bottom with the space geometric relationship therebetween is regarded as an advanced vehicle likelihood region, thereby detecting a vehicle.
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Abstract
A vehicle detection method includes (1) vehicle likelihood region identifying step; (2) vehicle component locating step; and (3) vehicle detecting step. To reduce complexity of calculation and enhance accuracy of detection, the method uses a vehicle likelihood region identifying algorithm to eliminate background regions from a total thermal image and keep vehicle likelihood regions therein for use in further analysis and processing, detects obvious vehicle components, such as vehicle windows and vehicle bottoms, in the thermal image to thereby identify vehicle component likelihood regions, describes a space geometric relationship of vehicle components with a Markov random field model, defines vehicle detection as problems with maximum a posteriori probability, estimates the most likely configuration with an optimization algorithm, so as to effectuate vehicle detection.
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Citations
9 Claims
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1. A vehicle detection method based on thermal imaging, adapted to capture a total thermal image of a specific region, the vehicle detection method comprising:
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an initial vehicle likelihood region identifying step in which a signature cutting algorithm discerns an initial vehicle likelihood regions and a background region in the total thermal image and deducts the background region by a background deduction technique to identify the initial vehicle likelihood region; a vehicle window locating step in which a border detection algorithm and a Hough transform detect an object component which has a feature that a pair of parallel horizontal lines are shown in a thermal image of the initial vehicle likelihood regions and a feature that a center of the thermal image is of low brightness, and the object component is regarded as a located vehicle window; a vehicle bottom locating step in which the border detection algorithm and the Hough transform detect an object component which has a feature that a thermal image of the initial vehicle likelihood regions is slender and a feature that the thermal image is of high brightness, and the object component is regarded as a located vehicle bottom; and a vehicle detecting step in which a space geometric relationship of the located vehicle window and vehicle bottom is described with a Markov random field, wherein, if the space geometric relationship conforms with a predetermined space geometric relationship, a region having the vehicle window and vehicle bottom with the space geometric relationship therebetween is regarded as an advanced vehicle likelihood region, thereby detecting a vehicle. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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Specification