Abstract: The present disclosure discloses a picture recognition method performed by a computing device. The method includes: obtaining a recognized current string and a hash value of the current string during text recognition for an acquired image through an optical character recognition model, and storing the current string and the hash value of the current string into a first preset tree structure and a second preset tree structure; predicting a new probability value of the current string at a next moment, to obtain an extended string set; obtaining N strings with the highest probability value according to the hash value stored in the second preset tree structure and retaining the N strings; and using the N strings as the current strings, repeating the foregoing steps until recognition of all acquired images is completed, and obtaining a string with the highest probability value as a final recognition result.

Abstract: The present disclosure discloses a picture recognition method performed by a computing device. The method includes: obtaining a recognized current string and a hash value of the current string during text recognition for an acquired image through an optical character recognition model, and storing the current string and the hash value of the current string into a first preset tree structure and a second preset tree structure; predicting a new probability value of the current string at a next moment, to obtain an extended string set; obtaining N strings with the highest probability value according to the hash value stored in the second preset tree structure and retaining the N strings; and using the N strings as the current strings, repeating the foregoing steps until recognition of all acquired images is completed, and obtaining a string with the highest probability value as a final recognition result.

Abstract: Some aspects of the disclosure provide a method for image processing. The method includes receiving one or more first images corresponding to first portions in a section of characters for recognition, splicing the one or more first images into a first intermediate spliced image and performing a first intermediate character recognition on the first intermediate spliced image based on a first optical character recognition model. The first intermediate character recognition generates a first intermediate recognition result for display. The method further includes performing a final character recognition on a final spliced image corresponding to the section of characters for recognition based on a second optical character recognition model that is different from the first optical character recognition model. The final character recognition generates a final recognition result of the section of characters. Apparatus and non-transitory computer-readable storage medium counterpart embodiments are also contemplated.