Gated Layer-Wise Text Image Rectification for Scene Distortion
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Text images captured in natural scenes often suffer from distortions such as twisting, bending, or wrinkling, which affect their quality and hinder applications like text recognition and navigation services.
Innovation Solution
A method involving layer-wise processing based on a gating strategy is applied to text images, increasing attention to structural features through channel, fine-grain, and coarse-grain layer levels to rectify the images, using a text image rectification model with encoders and decoders to improve rectification quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional text image processing is used, then the processing speed is fast, but the rectification quality is poor due to distortions
Solution Approach 1:
The patent divides the text image processing into multiple layer levels (first layer level, second layer level, etc.) with distinct processing tasks. The first layer level performs initial feature extraction and distortion detection, while subsequent layers perform progressive rectification. This segmentation allows each layer to focus on specific aspects of rectification, improving overall quality without overwhelming complexity in a single processing step.
Solution Approach 2:
The patent introduces a gating strategy that operates in an additional control dimension, dynamically adjusting the attention weights between different layer levels and processing stages. This gating mechanism adds a control layer that regulates information flow, enabling the system to adaptively allocate computational resources across different processing dimensions to optimize both quality and efficiency.
2Measurement precision
If attention is increased to text structural features, then the rectification accuracy is improved, but the computational cost increases
Solution Approach 1:
The gating strategy applies local quality control by dynamically adjusting attention weights differentially across spatial locations and feature channels. Instead of uniformly increasing attention everywhere, the system identifies and amplifies attention to specific regions and features that are most critical for rectification, such as text boundaries and structural elements, while maintaining lower attention weights for less informative regions, thus optimizing the computational cost-quality tradeoff.
Solution Approach 2:
The gating mechanism introduces dynamic adaptability by adjusting attention weights in real-time based on the input image characteristics and processing stage. The gating function dynamically modulates the flow of information between layers, allowing the system to increase computational attention to structural features when needed and reduce attention when features are already sufficiently processed, thereby optimizing computational resource utilization.
3Manufacturing precision
If multiple layer-wise processing is performed, then the rectification quality is improved, but the processing time increases
Solution Approach 1:
The patent implements continuous processing across multiple layer levels where each layer builds upon the output of the previous layer in a sequential manner. The gating strategy ensures continuous useful action by maintaining active information flow between layers, preventing idle computational cycles. This continuous processing approach allows the system to progressively refine rectification quality while keeping the processing pipeline fully utilized, optimizing the time-quality relationship.
Solution Approach 2:
The first layer level performs preliminary actions by extracting initial features, detecting distortions, and preparing processing targets before subsequent layers perform more complex rectification operations. This preliminary processing reduces the computational burden on later layers by pre-organizing and pre-processing the data, thereby shortening the overall processing time while maintaining high rectification quality through the cumulative effect of multiple layers.
Data Source
AI summary
A method of rectifying a text image, a training method, an electronic device, and a medium, which relate to a field of an artificial intelligence technology, in particular to fields of computer vision, deep learning technology, intelligent transportation and high-precision maps. An exemplary implementation includes: performing, based on a gating strategy, a plurality of first layer-wise processing on a text image to be rectified, so as to obtain respective feature maps of a plurality of layer levels, wherein each of the feature maps includes a text structural feature related to the text image to be rectified, and the gating strategy is configured to increase an attention to the text structural feature; and performing a plurality of second layer-wise processing on the respective feature maps of the plurality of layer levels, so as to obtain a rectified text image corresponding to the text image to be rectified.