Method and apparatus for arbitrary output shape processing of an image

Patent metadata

Field	Value
Publication number	US-11915442-B2
Application number	US-202117474489-A
Country	US
Kind code	B2
Filing date	Sep 14, 2021
Priority date	Sep 25, 2017
Publication date	Feb 27, 2024
Grant date	Feb 27, 2024

Abstract

An apparatus and method for geometrically correcting an arbitrary shaped input frame and generating an undistorted output frame. The method includes capturing arbitrary shaped input images with multiple optical devices and processing the images, identifying redundant blocks and valid blocks in each of the images, allocating an output frame with an output frame size and dividing the output frame into regions shaped as a rectangle, programming the apparatus and disabling processing for invalid blocks in each of the regions, fetching data corresponding to each of the valid blocks and storing in an internal memory, interpolating data for each of the regions with stitching and composing the valid blocks for the output frame and displaying the output frame on a display module.

First claim

We claim:

1. A method comprising:
capturing, by a first optical device, a first image;
capturing, by a second optical device, a second image;
mapping, by a processor, blocks of an output frame to the first and second images;
determining, by the processor, scaling data for each of the blocks of the output frame;
determining, by the processor, at least one scaling threshold based on the scaling data;
dividing, by the processor, the output frame into one or more regions based on the at least one scaling threshold; and
determining, by the processor, a respective block size for each of the one or more regions of the output frame based on the scaling data and the at least one scaling threshold.

2. The method of claim 1 , wherein:
the first optical device includes one of a first wide angle lens, a first fish eye lens, or a first automotive camera lens; and
the second optical device includes one of a second wide angle lens, a second fish eye lens, or a second automotive camera lens.

3. The method of claim 1 , wherein:
the first image and the second image have an arbitrary shape; and
the arbitrary shape is square, rectangle, oval, or elongated.

4. The method of claim 1 , wherein:
the processor stores the first image and the second image in external memory.

5. The method of claim 1 , further comprising:
identifying, by the processor, a block of at least one of the one or more regions as a redundant block; and
skipping, by the processor, some processing of the at least one region that includes the redundant block.

6. The method of claim 5 , wherein:
identifying a block of at least one of the one or more regions as a redundant block further comprises comparing data of the first image and data of the second image and identifying that the block is mapped to duplicate data between the first and second images.

7. The method of claim 1 , wherein:
the output frame has an output frame size.

8. The method of claim 1 , wherein:
the one or more regions of the output frame are rectangular.

9. The method of claim 1 , further comprising:
applying, by the processor, a perspective transformation to determine coordinates of blocks in the first and second images corresponding to the blocks of the output frame.

10. The method of claim 1 , wherein:
the output frame includes a first region and a second region;
the block size of the first region includes a first block width and a first block height; and
the block size of the second region includes a second block width and a second block height.

11. An apparatus comprising:
a first optical device configured to capture a first image;
a second optical device configured to capture a second image; and
a processor configured to:
map blocks of an output frame to the first and second images;
determine scaling data for each of the blocks of the output frame;
determine at least one scaling threshold based on the scaling data;
divide the output frame into one or more regions based on the at least one scaling threshold; and
determine a respective block size for each of the one or more regions of the output frame based on the scaling data and the at least one scaling threshold.

12. The apparatus of claim 11 , wherein:
the first optical device includes one of a first wide angle lens, a first fish eye lens, or a first automotive camera lens; and
the second optical device includes one of a second wide angle lens, a second fish eye lens, or a second automotive camera lens.

13. The apparatus of claim 11 , wherein:
the first image and the second image have an arbitrary shape; and
the arbitrary shape is square, rectangle, oval, or elongated.

14. The apparatus of claim 11 , wherein:
the processor stores the first image and the second image in external memory.

15. The apparatus of claim 11 , wherein the processor is further configured to:
identify a block of at least one of the one or more regions as a redundant block; and
skip some processing of the at least one region that includes the redundant block.

16. The apparatus of claim 15 , wherein:
to identify a block of at least one of the one or more regions as a redundant block, the processor is configured to compare data of the first image and data of the second image and identify that the block is mapped to duplicate data between the first and second images.

17. The apparatus of claim 11 , wherein:
the output frame has an output frame size.

18. The apparatus of claim 11 , wherein:
the one or more regions of the output frame are rectangular.

19. The apparatus of claim 11 , wherein:
the processor is configured to apply a perspective transformation to determine coordinates of blocks in the first and second images corresponding to the blocks of the output frame.

20. The apparatus of claim 11 , wherein:
the output frame includes a first region and a second region;
the block size of the first region includes a first block width and a first block height; and
the block size of the second region includes a second block width and a second block height.

Assignees

• Texas Instruments Inc

Inventors

• Allu Rajasekhar Reddy
• Nandan Niraj
• Mody Mihir Narendra
• Hua Gang
• Chae Brian Okchon
• Dabral Shashank
• Sanghvi Hetul
• Appia Vikram Vijayanbabu
• Shivalingappa Sujith

Classifications

• G06T7/60 Primary

  Analysis of geometric attributes · CPC title

• G06T5/006

  Physics · mapped topic

• G06T5/40

  using histogram techniques · CPC title

• G06T7/11

  Region-based segmentation · CPC title

• G06T2207/10024

  Color image · CPC title