Calibration of fixed image-capturing device for predicting driving lane

1. A method, comprising:

identifying, by circuitry, in a first image including a plurality of lines on a calibration lane of a first object, a first plurality of rows of pixels corresponding to the plurality of lines perpendicular to the calibration lane;

determining, by the circuitry, from the first image, a first width of a first line corresponding to a first row of pixels of the first plurality of rows of pixels;

determining, by the circuitry, a second width of a second line corresponding to a second row of pixels of a second plurality of rows of pixels in the first image based on at least the first width and an angle between the first line and the second line, wherein the angle is formed by joining endpoints of the first line and the second line;

estimating, by the circuitry, column values for each line corresponding to each row of pixels in the first image based on at least one of the first width or the second width associated with a corresponding line; and

storing, by the circuitry in a memory, the estimated column values for each line, wherein a driving lane for the first object is predicted based on the stored column values, and wherein a second object in a second image is analyzed for impending collision with the first object when the second object is detected in the driving lane of the first object.

2. The method of claim 1 , further comprising:

converting, by the circuitry, the first image from a first color model to a second color model; and

filtering, by the circuitry, the converted first image to obtain a filtered first image including a predetermined color,

wherein the plurality of lines is identified from the first image by executing edge detection of the filtered first image.

3. The method of claim 2 , wherein the first and second color models are at least one of a black and white color model, a greyscale color model, a red, green, and blue (RGB) color model, a hue, saturation, and value (HSV) color model, a cyan, magenta, yellow, and black (CMYK) color model, a hue, saturation, and brightness (HSB) color model, a hue, saturation, and lightness (HSL) color model, or a hue, chroma, and value (HCV) color model, and wherein the first color model is different from the second color model.

4. The method of claim 1 , wherein the first image comprises the first and second pluralities of rows of pixels.

5. The method of claim 1 , further comprising:

detecting, by the circuitry, a bottom edge, a first side edge, a second side edge, and a top edge of the second object in the second image;

generating, by the circuitry, a bounding box including the second object based on the bottom edge, the first side edge, the second side edge, and the top edge; and

estimating, by the circuitry, an overlapping area between the bounding box and the driving lane, wherein the second object is detected for the impending collision when the overlapping area is greater than or equal to a threshold area.

6. The method of claim 5 , further comprising:

generating, by the circuitry, a warning message based on at least a distance of the second object from the first object, when the overlapping area is greater than or equal to the threshold area; and

communicating, by the circuitry to an entity associated with the first object, the warning message indicating the impending collision.

7. The method of claim 1 , wherein the first image and the second image are captured by an image-capturing device that is mounted at a center of the first object such that the first image and the second image are equally divided into two halves along an axis passing via the image-capturing device, and wherein the first image and the second image include an equal number of row pixels and column pixels.

8. The method of claim 7 , wherein the first width and the second width are determined in terms of number of column pixels in the first image.

9. A method, comprising:

identifying, by circuitry, in a first image of a calibration lane of a first object, a plurality of lines parallel to the calibration lane;

determining, by the circuitry, for each row of pixels in the first image, an observed width between the plurality of lines;

estimating, by the circuitry, for each row of pixels in the first image, column values based on the observed width of a corresponding row of pixels, a first object width of the first object, and an actual lane width between the plurality of lines; and

storing, by the circuitry in a memory, the estimated column values for each row of pixels, wherein a driving lane for the first object is predicted based on the stored column values, and wherein a second object in a second image is analyzed for impending collision with the first object when the second object is detected in the driving lane of the first object.

10. The method of claim 9 , further comprising:

converting, by the circuitry, the first image from a first color model to a second color model; and

filtering, by the circuitry, the converted first image to obtain a filtered first image including a predetermined color,

wherein the plurality of lines is identified from the first image by executing edge detection of the filtered first image.

11. The method of claim 10 , wherein the first and second color models are at least one of a black and white color model, a greyscale color model, a red, green, and blue (RGB) color model, a hue, saturation, and value (HSV) color model, a cyan, magenta, yellow, and black (CMYK) color model, a hue, saturation, and brightness (HSB) color model, a hue, saturation, and lightness (HSL) color model, or a hue, chroma, and value (HCV) color model, and wherein the first color model is different from the second color model.

12. The method of claim 9 , further comprising:

detecting, by the circuitry, a bottom edge, a first side edge, a second side edge, and a top edge of the second object in the second image;

generating, by the circuitry, a bounding box including the second object based on the bottom edge, the first side edge, the second side edge, and the top edge; and

estimating, by the circuitry, an overlapping area between the bounding box and the driving lane, wherein the second object is detected for the impending collision when the overlapping area is greater than or equal to a threshold area.

13. The method of claim 12 , further comprising:

generating, by the circuitry, a warning message based on at least a distance of the second object from the first object, when the overlapping area is greater than or equal to the threshold area; and

communicating, by the circuitry to an entity associated with the first object, the warning message indicating the impending collision.

14. The method of claim 9 , wherein the first image and the second image are captured by an image-capturing device that is mounted at a center of the first object such that the first image and the second image are equally divided into two halves along an axis passing via the image-capturing device.

15. The method of claim 14 , wherein the first image and the second image include an equal number of row pixels and column pixels, and wherein the observed width is determined in terms of the number of column pixels in the first image.

16. A system, comprising:

circuitry configured to:

identify, in a first image of a calibration lane of a first object, a plurality of lines parallel to the calibration lane;

determine, for each row of pixels in the first image, an observed width between the plurality of lines;

estimate, for each row of pixels in the first image, column values based on the observed width of a corresponding row of pixels, a first object width of the first object, and an actual lane width between the plurality of lines; and

store the estimated column values for each row of pixels in a memory, wherein a driving lane for the first object is predicted based on the stored column values, and wherein a second object in a second image is analyzed for impending collision with the first object when the second object is detected in the driving lane of the first object.

17. The system of claim 16 , wherein the circuitry is further configured to:

convert the first image from a first color model to a second color model; and

filter the converted first image to obtain a filtered first image that includes a predetermined color,

wherein the plurality of lines is identified from the first image based on execution of edge detection of the filtered first image.

18. The system of claim 16 , wherein the circuitry is further configured to:

detect a bottom edge, a first side edge, a second side edge, and a top edge of the second object in the second image;

generate a bounding box that includes the second object based on the bottom edge, the first side edge, the second side edge, and the top edge; and

estimate an overlapping area between the bounding box and the driving lane, wherein the second object is detected for the impending collision when the overlapping area is greater than or equal to a threshold area.

19. The system of claim 18 , wherein the circuitry is further configured to:

generate a warning message based on at least a distance of the second object from the first object, when the overlapping area is greater than or equal to the threshold area; and

communicate the warning message to an entity associated with the first object, wherein the warning message indicates the impending collision.

20. The system of claim 16 , wherein the first image and the second image are captured by an image-capturing device that is mounted at a center of the first object such that the first image and the second image are equally divided into two halves along an axis that passes via the image-capturing device, and wherein the first image and the second image include an equal number of row pixels and column pixels, and wherein the observed width is determined in terms of the number of column pixels in the first image.