Text detection in video
View Patent ↗Techniques of detecting text in video are disclosed. In some embodiments, a portion of video content can be identified as having text. Text within the identified portion of the video content can be identified. A category for the identified text can be determined. In some embodiments, a determination is made as to whether the video content satisfies at least one predetermined condition, and the portion of video content is identified as having text in response to a determination that the video content satisfies the predetermined condition(s). In some embodiments, the predetermined condition(s) comprises at least one of a minimum level of clarity, a minimum level of contrast, and a minimum level of content stability across multiple frames. In some embodiments, additional information corresponding to the video content is determined based on the identified text and the determined category.
1. A computer-implemented method comprising:
identifying, by a machine having a memory and at least one processor, a portion of video content as having text, the identifying comprising:
converting a frame of the video content to grayscale;
performing edge detection on the frame;
performing dilation on the frame to connect vertical edges within the frame;
binarizing the frame;
performing a connected component analysis on the frame to detect connected components within the frame;
merging the connected components into a plurality of text lines;
refining the plurality of text lines using horizontal and vertical projections;
filtering out at least one of the plurality of text lines based on a size of the at least one of the plurality of text lines to form a filtered set of text lines;
binarizing the filtered set of text lines; and
filtering out at least one of the text lines from the binarized filtered set of text lines based on at least one of a shape of components in the at least one of the text lines and a position of components in the at least one of the text lines to form the portion of the video content having text;
identifying text within the identified portion of the video content; and
determining a category for the identified text.
2. The method of claim 1 , further comprising determining whether the video content satisfies at least one predetermined condition, wherein performing the identifying of the portion of video content as having text is conditioned upon a determination that the video content satisfies the at least one predetermined condition.
3. The method of claim 2 , wherein the at least one predetermined condition comprises at least one of a minimum level of clarity, a minimum level of contrast, and a minimum level of content stability across multiple frames.
4. The method of claim 1 , further comprising determining additional information corresponding to the video content based on the identified text and the determined category.
5. The method of claim 4 , further comprising causing the additional information to be displayed on a media content device.
6. The method of claim 4 , further comprising storing the additional information in association with the video content or in association with an identified viewer of the video content.
7. The method of claim 4 , further comprising providing the additional information to a software application on a media content device.
8. The method of claim 7 , wherein the additional information comprises at least one of a uniform resource locator (URL), an identification of a user account, a metadata tag, and a phone number.
9. The method of claim 7 , wherein the media content device comprises one of a television, a laptop computer, a desktop computer, a tablet computer, and a smartphone.
10. The method of claim 1 , further comprising storing the identified text in association with the video content or in association with an identified viewer of the video content.
11. The method of claim 1 , wherein identifying text within the identified portion of the video content comprises performing optical character recognition on the identified portion of the video content.
12. The method of claim 1 , wherein determining the category for the identified text comprises:
parsing the identified text to determine a plurality of segments of the identified text; and
determining the category based on a stored association between at least one of the plurality of segments and the category.
13. The method of claim 1 , wherein the video content comprises a portion of a television program, a non-episodic movie, a webisode, user-generated content for a video-sharing website, or a commercial.
14. A system comprising:
a machine having a memory and at least one processor; and
at least one module on the machine, the at least one module being configured to:
identify a portion of video content as having text, the identifying comprising:
converting a frame of the video content to grayscale;
performing edge detection on the frame;
performing dilation on the frame to connect vertical edges within the frame;
binarizing the frame;
performing a connected component analysis on the frame to detect connected components within the frame;
merging the connected components into a plurality of text lines;
refining the plurality of text lines using horizontal and vertical projections;
filtering out at least one of the plurality of text lines based on a size of the at least one of the plurality of text lines to form a filtered set of text lines:
binarizing the filtered set of text lines; and
filtering out at least one of the text lines from the binarized filtered set of text lines based on at least one of a shape of components in the at least one of the text lines and a position of components in the at least one of the text lines to form the portion of the video content having text;
identify text within the identified portion of the video content; and
determine a category for the identified text.
15. The system of claim 14 , wherein the at least one module is further configured to:
determine whether the video content satisfies at least one predetermined condition; and
identify the portion of video content as having text in response to a determination that the video content satisfies the at least one predetermined condition.
16. The system of claim 15 , wherein the at least one predetermined condition comprises at least one of a minimum level of clarity, a minimum level of contrast, and a minimum level of content stability across multiple frames.
17. The system of claim 14 , wherein the at least one module is further configured to determine additional information corresponding to the video content based on the identified text and the determined category.
18. The system of claim 17 , wherein the at least one module is further configured to provide the additional information to a software application on a media content device.
19. A non-transitory machine-readable storage device, tangibly embodying a set of instructions that, when executed by at least one processor, causes the at least one processor to perform a set of operations comprising:
identifying a portion of video content as having text, the identifying comprising:
converting a frame of the video content to grayscale;
performing edge detection on the frame;
performing dilation on the frame to connect vertical edges within the frame;
binarizing the frame;
performing a connected component analysis on the frame to detect connected components within the frame;
merging the connected components into a plurality of text lines;
refining the plurality of text lines using horizontal and vertical projections;
filtering out at least one of the plurality of text lines based on a size of the at least one of the plurality of text lines to form a filtered set of text lines;
binarizing the filtered set of text lines; and
filtering out at least one of the text lines from the binarized filtered set of text lines based on at least one of a shape of components in the at least one of the text lines and a position of components in the at least one of the text lines to form the portion of the video content having text;
identifying text within the identified portion of the video content; and
determining a category for the identified text.