Projective Distortion Correction for Text-Rich Images
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Solution Overview
Problem
Existing methods for correcting projective distortion in digital images are either manual, time-consuming, error-prone, or require complex parameter settings, and are not effective for images with a combination of text and pictures or non-standard formatting, especially in resource-constrained devices like mobile communication devices.
Innovation Solution
A method involving image binarization, connected component analysis, horizontal and vertical vanishing point determination using eigenpoints and confidence levels, and projective correction based on these points to automatically correct perspective distortion in images, specifically focusing on textual information and separating text from pictures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual correction techniques are used to identify and mark corners or parallel lines, then projective distortion correction can be performed, but the process becomes time-consuming and inefficient
Solution Approach 1:
The system automatically identifies text regions and determines vanishing points without requiring manual user input. The algorithm self-corrects projective distortion by detecting text baselines and computing vanishing points from the image content itself, eliminating the need for users to manually mark corners or lines while maintaining high correction accuracy
Solution Approach 2:
The patent replaces manual mechanical interaction (user marking corners/lines) with an automated computer vision system that uses image processing algorithms to detect text regions, compute eigenpoints, and determine vanishing points automatically, thereby substituting human operation with computational processes
2Extent of automation
If existing automatic correction techniques are used that focus on identifying vanishing points, then projective distortion can be corrected, but complicated manual parameter settings are still required
Solution Approach 1:
The system automatically adapts to different image contents by detecting text regions and computing vanishing points specific to each image. It requires no manual parameter settings as the algorithm self-configures based on the detected text baseline orientations and eigenpoints, making it fully automatic and easy to operate across various document types
Solution Approach 2:
The patent implements dynamic parameter adaptation where the correction parameters (vanishing points, transformation matrices) are computed automatically based on the specific image content. The system dynamically adjusts to different text layouts, orientations, and document types without requiring pre-configured parameters or manual intervention
3Manufacturing precision
If existing correction techniques are used that assume documents comprise only text in particular formatting, then correction can be performed for standardized documents, but the techniques fail for images with mixed content or non-standard formatting
Solution Approach 1:
The patent creates a universal correction system that handles multiple document types including text-only documents, mixed text-picture documents, and non-standard formatted documents. The algorithm universally applies text region detection and vanishing point computation regardless of document content composition, making it adaptable to various formatting scenarios while maintaining correction accuracy
Solution Approach 2:
The system dynamically changes its processing parameters based on detected text region characteristics. It adapts the vanishing point computation method according to the actual text baseline orientations and eigenpoint distributions in the image, allowing it to handle non-standard formatting and mixed content effectively by adjusting to the specific geometric properties of each document
4Reliability
If existing automatic correction techniques are used, then projective distortion correction can be performed, but the computational cost is high making it difficult to implement in mobile devices
Solution Approach 1:
The patent extracts only the essential features needed for correction: text region detection, eigenpoint computation from text baselines, and vanishing point determination. By focusing computation only on relevant text elements rather than processing the entire image, it reduces computational energy consumption while maintaining correction accuracy suitable for mobile devices
Data Source
AI summary
Method, system, device and computer program product for projective correction of an image containing at least one text portion that is distorted by perspective. The method includes the steps of image binarization, connected component analysis, horizontal vanishing point determination, vertical vanishing point determination and projective correction. The horizontal vanishing point is determined by estimating text baselines by means of position determining pixels of pixel blobs, identifying horizontal vanishing point candidates from the baselines, and determining a horizontal vanishing point from the candidates. The vertical vanishing point is determined on the basis of vertical features of the text portion. The method includes a first elimination step on the level of position determining pixels, a second elimination step on the level of text baselines and a third elimination step on the level of horizontal vanishing point candidates.