OCR Region Orientation for Barcode-Free Text Recognition
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional optical character recognition (OCR) technologies struggle to effectively identify text strings without associated barcodes, requiring manual device rotation or barcode scanning to determine orientation, which is inefficient and resource-intensive.
Innovation Solution
The method involves determining a composite directionality condition of a text string, including reading direction and character orientation, to perform OCR operations within a targeted region of interest (ROI) without barcode scanning, using user input or object detection to adjust the ROI's size, position, and rotation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual device rotation is used to orient text string horizontally, then OCR accuracy is improved, but user operation complexity and time consumption increase
Solution Approach 1:
The system automatically detects text string orientation and rotates the ROI window to match the text direction without requiring manual user intervention. The computing device performs self-adjustment by analyzing the detected text string's reading direction and character orientation, then autonomously orients the OCR processing window accordingly.
Solution Approach 2:
The system performs preliminary detection of the text string's composite directionality condition (reading direction and character orientation) before executing the OCR operation. By pre-orienting the ROI window based on detected text orientation, the system prepares the optimal processing state in advance, ensuring accurate OCR results without requiring subsequent manual adjustments.
2Extent of automation
If barcode scanning is used to determine orientation, then text string orientation can be automatically identified, but applicability is limited to cases with barcodes
Solution Approach 1:
The system replaces the barcode-based orientation detection mechanism with direct text string analysis. Instead of relying on barcode patterns to infer orientation, the system directly analyzes the geometric and directional properties of the detected text string itself, substituting a more versatile detection approach that works with any text string regardless of accompanying barcodes.
Solution Approach 2:
The orientation detection system is designed to handle multiple scenarios universally: it can detect text strings with barcodes, without barcodes, in various orientations (horizontal, vertical, rotated), and on different types of objects. The composite directionality condition analysis provides a unified approach that adapts to diverse application contexts, enhancing system versatility.
3Measurement precision
If full image processing is performed for OCR, then all text strings can be identified, but processing time and computational resources increase
Solution Approach 1:
The system segments the processing task by first detecting the text string's location and composite directionality condition, then creating a focused ROI window that encompasses only the relevant text region. This segmentation allows the OCR engine to process only the necessary portion of the image rather than analyzing the entire image, significantly reducing computational load while maintaining complete text string identification within the targeted area.
Solution Approach 2:
The system applies different processing quality levels to different regions: high-resolution OCR processing is applied only to the detected text string region within the ROI window, while the rest of the image receives minimal or no processing. This local quality approach ensures accurate text recognition where needed while conserving computational resources in non-critical areas.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Embodiments of the present disclosure provide systems and methods for optical character recognition (OCR) using targeted regions of interest (ROIs). In one embodiment, a method includes receiving, by one or more processors, data representative of an image comprising a text string, causing, by the one or more processors, a user interface to display the image comprising the text string, causing, by the one or more processors, the user interface to display a window on the image, the window representative of a region for performing an OCR operation, and performing, by the one or more processors, the OCR operation for the region based at least in part on a composite directionality condition of the text string. In some examples, the composite directionality condition of the text string includes a reading direction of the text string and a character orientation of the text string.