Method and a System For Detecting a Road at Night
First Claim
1. A method for detecting a road at night or in poor visual conditions, said method being based on an image frame and being executed by a computer, said image frame, I, being divided into pixels, each having an intensity value assigned corresponding to a temperature of a point of an environment that the image frame represents, said method comprising the steps ofcalculating a mask, R, (230) by detecting in said image frame pixels candidating to represent a road;
- selecting (250) from the road candidate pixels an initial cluster of road candidate pixels having a lower boundary coinciding with or being located in the vicinity of the lower part of the image frame as an estimate of the road;
determining an initial horizon estimate (240) as a first horizontally oriented boundary between horizontal regions characterized by different densities of road candidate pixels;
defining a final road cluster (260) by correcting the selected initial cluster of road candidate pixels (250) having an upper boundary, said correction being based on the location of said upper boundary relative to the initially estimated horizon and a predetermined upper limit for the location of the horizon.
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Abstract
A method of detecting a road feature in an image signal derived from an infrared-sensitive camera. The method, in overview, comprises processing an image frame by assigning binary values to pixels in the frame in response to their representative temperature, and then to analyze spatially the binary mask to identify regions of pixels having mutually similar assigned binary values. The road feature is subsequently found from the analysis of the identified regions of mutually similar binary values and a visual indication of the road feature in relation to the image frame provided to the user.
27 Citations
15 Claims
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1. A method for detecting a road at night or in poor visual conditions, said method being based on an image frame and being executed by a computer, said image frame, I, being divided into pixels, each having an intensity value assigned corresponding to a temperature of a point of an environment that the image frame represents, said method comprising the steps of
calculating a mask, R, (230) by detecting in said image frame pixels candidating to represent a road; -
selecting (250) from the road candidate pixels an initial cluster of road candidate pixels having a lower boundary coinciding with or being located in the vicinity of the lower part of the image frame as an estimate of the road; determining an initial horizon estimate (240) as a first horizontally oriented boundary between horizontal regions characterized by different densities of road candidate pixels; defining a final road cluster (260) by correcting the selected initial cluster of road candidate pixels (250) having an upper boundary, said correction being based on the location of said upper boundary relative to the initially estimated horizon and a predetermined upper limit for the location of the horizon. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 15)
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10. A system for detecting a road at night or in poor visual conditions, the system comprising one or more data processors and one or more data memories, the system is storing data in the one or more memories representing an image frame, I, being divided into pixels, each having an intensity value assigned corresponding to a temperature of a point of an environment that the image frame represents, the system is provided with instructions which upon execution by the one or more processors adapt the system to:
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calculating a mask, R, (230) by detecting in said image frame pixels candidating to represent a road; selecting (250) from the road candidate pixels an initial cluster of road candidate pixels having a lower boundary coinciding with or being located in the vicinity of the lower part of the image frame as an estimate of the road; determining an initial horizon estimate (240) as a first horizontally oriented boundary between horizontal regions characterized by different densities of road candidate pixels; defining a final road cluster (260) by correcting the selected initial cluster of road candidate pixels (250) having an upper boundary, said correction being based on the location of said upper boundary relative to the initially estimated horizon and a predetermined upper limit for the location of the horizon. - View Dependent Claims (11, 12, 13, 14)
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Specification