Automated Digital Image De-tilting via Edge Analysis
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Solution Overview
Problem
Digital images captured with tilted cameras or scanners often result in undesirably rotated images, with existing solutions requiring manual input to correct tilt, especially in images containing non-textual features.
Innovation Solution
An automated method that analyzes digital images to determine a dominant edge direction, selects an angle based on this direction, and rotates the image pixels to generate a de-tilted version, using edge detection, filtering, and histogram-based angle selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual tilt correction is used, then tilt removal accuracy is improved, but user input requirement increases operation complexity
Solution Approach 1:
The system automatically detects edges, determines dominant orientations, and corrects tilt without requiring user input. The image processing algorithm independently identifies the tilt angle through edge analysis and applies correction automatically, making the system self-sufficient and eliminating manual intervention.
Solution Approach 2:
The system transforms the image by applying a rotation transformation parameter based on the detected dominant edge orientation. By changing the orientation parameter of the image pixels, the system achieves automatic tilt correction while maintaining accuracy.
2Ease of operation
If automatic deskew is used for text documents, then operation simplicity is improved, but applicability to non-textual images deteriorates
Solution Approach 1:
The edge detection-based tilt correction system is universally applicable to all types of images including photographs, scanned documents, and non-textual images. Unlike text-specific deskew algorithms, this system works with any image containing edge structures, making it multi-functional and highly adaptable.
Solution Approach 2:
The patent replaces text-specific recognition mechanisms with general edge detection and orientation analysis mechanisms. By substituting the specialized text analysis system with a universal edge-based geometric analysis system, the solution achieves broad applicability across different image types while maintaining automatic operation.
3Extent of automation
If edge detection and angle analysis are performed, then automatic tilt correction capability is improved, but processing complexity increases
Solution Approach 1:
The image processing is segmented into distinct stages: edge detection, edge filtering, dominant orientation determination, and image rotation. By dividing the complex automatic correction process into manageable segments, the system achieves high automation while keeping each processing stage relatively simple and well-defined.
Data Source
AI summary
Tilt is reduced or eliminated in captured digital images. Edges in a first image are detected. Angles corresponding to the detected edges are determined. A dominant angle is selected from the determined angles. The first image is rotated according to the selected dominant angle to generate a second image. The second image is a de-tilted version of the first image.