Invention Grant
- Patent Title: Local connectivity feature transform of binary images containing text characters for optical character/word recognition
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Application No.: US15721610Application Date: 2017-09-29
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Publication No.: US10521697B2Publication Date: 2019-12-31
- Inventor: Shubham Agarwal , Maral Mesmakhosroshahi , Yongmian Zhang
- Applicant: KONICA MINOLTA LABORATORY U.S.A., INC.
- Applicant Address: US CA San Mateo
- Assignee: KONICA MINOLTA LABORATORY U.S.A., INC.
- Current Assignee: KONICA MINOLTA LABORATORY U.S.A., INC.
- Current Assignee Address: US CA San Mateo
- Agency: Chen Yoshimura LLP
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06K9/34 ; G06K9/36 ; G06K9/66 ; G06T7/45 ; G06N3/04

Abstract:
A local connectivity feature transform (LCFT) is applied to binary document images containing text characters, to generate transformed document images which are then input into a bi-directional Long Short Term Memory (LSTM) neural network to perform character/word recognition. The LCFT transformed image is a gray scale image where the pixel values encode local pixel connectivity information of corresponding pixels in the original binary image. The transform is one that provides a unique transform score for every possible shape represented as a 3×3 block. In one example, the transform is computed using a 3×3 weight matrix that combines bit coding with a zigzag pattern to assign weights to each element of the 3×3 block, and by summing up the weights for the non-zero elements of the 3×3 block shape.
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