Image Processing Apparatus for Low-Resolution Character Recognition
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Solution Overview
Problem
Current OCR processes for character images captured by cameras face significant challenges with low-resolution images, where recognition rates are severely reduced and vary greatly due to photography conditions, leading to difficulties in determining final characters, especially when high-quality images cannot be obtained.
Innovation Solution
An image processing apparatus and method that extracts and compares character strings from multiple images captured from different angles and positions, calculating similarity degrees and using weighting factors based on positional and pixel information to enhance recognition precision, allowing for accurate character string recognition even with low-resolution images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If OCR process is executed on low-resolution character images, then more character images can be processed, but recognition rate extremely lowers
Solution Approach 1:
The patent combines multiple low-resolution character images showing the same document into a single high-quality image through super-resolution processing. By merging redundant information from multiple images, the system reconstructs a high-resolution image that maintains accurate character recognition while enabling processing of originally low-resolution inputs.
Solution Approach 2:
The patent transitions from processing individual low-resolution 2D images to utilizing multiple 2D images in a temporal dimension (captured at different times) to create a high-resolution output. This multi-dimensional approach allows the system to overcome resolution limitations by leveraging information across multiple image captures.
2Measurement precision
If OCR process is executed on only high-quality character images, then recognition rate is maintained, but all character images are excluded when high-quality images cannot be obtained
Solution Approach 1:
The patent converts the harmful effect of multiple photographs taken under varying conditions into a beneficial resource. By using these previously discarded low-quality images as input for super-resolution processing, the system transforms photography variability from a problem into a solution, enabling high recognition rates even when individual images are of poor quality.
3Quantity of substance
If OCR process is executed on plurality of character images photographed at different timings, then more data is available, but determination of final characters is difficult when recognition results divide
Solution Approach 1:
The patent performs super-resolution processing and image merging before the OCR recognition step. By pre-processing multiple images into a single high-quality image, the system eliminates the need to handle multiple separate recognition results, simplifying the determination process while maintaining high accuracy.
Data Source
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AI summary
According to one embodiment, an image processing apparatus includes a calculation unit and a recognition unit. The calculation unit is configured to calculate a first similarity degree group which is composed of similarity degrees between respective characters constituting a first character string appearing on a first image and respective candidate characters in a candidate character group, and to calculate a second similarity degree group which is composed of similarity degrees between respective characters constituting a second character string appearing on a second image and the respective candidate characters in the candidate character group.