Illumination invariant and robust apparatus and method for detecting and recognizing various traffic signs
First Claim
1. A method for detecting and recognizing traffic signs using images captured by a digital color and night vision camera, the said method characterized in being illumination invariant comprising:
- transforming, by a processor, RGB image into HSV color model and subsequently extracting desired color components by using color quantization;
filtering, by the processor, noise components in the HSV color model in order to obtain a filtered image, wherein the filtered image is obtained by,computing a centroid of each Region of Interest (ROI) in the HSV color model,calculating a left distance indicating a distance from the centroid to a plurality of left side elements present in the HSV color model,calculating a right distance indicating a distance from the centroid to a plurality of right side elements present in the HSV color model,filtering the noise components based on the left distance, the right distance, a count of the plurality of left side elements, and a count of the plurality of right side elements;
detecting, by the processor, edges of objects in the filtered image and subsequently detecting distinct objects in the filtered image;
classifying, by the processor, shapes of traffic signs based on shape of the distinct objects; and
recognizing, by the processor, the shapes of the traffic signs by template matching.
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Abstract
The present application provides a robust, illumination invariant apparatus and method for detecting and recognizing various traffic signs. A robust method for detecting and recognizing the traffic signs using images captured by a digital color and night vision camera, the said method characterized in being illumination invariant comprising the processor implemented steps of: transforming RGB image into HSV color model and subsequently extracting desired color components by using color quantization; filtering the noise components in the HSV color model based on object symmetrical shape property; detecting edges of the objects and subsequently detecting the distinct objects in the noise components filtered image; classifying the shapes of the traffic signs based on shape of the determined distinct objects; and recognizing the classified shapes of the traffic signs by template matching. Further, the method provides the provision for warning the driver by use of the recognized data of the traffic signs.
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Citations
11 Claims
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1. A method for detecting and recognizing traffic signs using images captured by a digital color and night vision camera, the said method characterized in being illumination invariant comprising:
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transforming, by a processor, RGB image into HSV color model and subsequently extracting desired color components by using color quantization; filtering, by the processor, noise components in the HSV color model in order to obtain a filtered image, wherein the filtered image is obtained by, computing a centroid of each Region of Interest (ROI) in the HSV color model, calculating a left distance indicating a distance from the centroid to a plurality of left side elements present in the HSV color model, calculating a right distance indicating a distance from the centroid to a plurality of right side elements present in the HSV color model, filtering the noise components based on the left distance, the right distance, a count of the plurality of left side elements, and a count of the plurality of right side elements; detecting, by the processor, edges of objects in the filtered image and subsequently detecting distinct objects in the filtered image; classifying, by the processor, shapes of traffic signs based on shape of the distinct objects; and recognizing, by the processor, the shapes of the traffic signs by template matching. - View Dependent Claims (2, 3, 4, 5, 6, 7, 11)
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8. An apparatus for detecting and recognizing traffic signs, the apparatus characterized in being illumination invariant, comprising of:
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a digital color and a night vision camera disposed on the vehicle for capturing an image; and a processor, coupled with a memory, embedded therein for analyzing the image in real-time for detecting and recognizing the traffic signs by; transforming RGB image into HSV color model and subsequently extracting desired color components by using color quantization; filtering noise components in the HSV color model in order to obtain a filtered image, wherein the filtered image is obtained by; computing a centroid of each Region of Interest (ROI) in the HSV color model, calculating a left distance indicating a distance from the centroid to a plurality of left side elements present in the HSV color model, calculating a right distance indicating a distance from the centroid to a plurality of right side elements present in the HSV color model, filtering the noise components based on the left distance, the right distance, a count of the plurality of left side elements, and a count of the plurality of right side elements; detecting edges of objects in the filtered image and subsequently detecting distinct objects in the filtered image; classifying shapes of traffic signs based on shape of the distinct objects; and recognizing the shapes of the traffic signs by template matching. - View Dependent Claims (9, 10)
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Specification