Baselines Extraction from Curved Document Images via Slope Fields Recovery

Area of Science:

• Document Image Analysis
• Computer Vision
• Geometric Methods

Background:

• Baseline estimation is crucial for document image processing.
• Complex layouts and image degradations pose significant challenges.
• Existing methods often rely on text-line detection, which can be limiting.

Purpose of the Study:

• To propose a robust method for curved baseline extraction from distorted document images.
• To overcome limitations of traditional text-line based approaches.
• To improve document image analysis for various challenging conditions.

Main Methods:

• A novel method based on slope field recovery for curved baseline extraction.
• Treating baselines as solution curves of an ordinary differential equation on a slope field.
• Estimating the slope field using intrinsic geometric constraints of baselines on a developable surface.
• Solving the ordinary differential equation using the Euler method.

Main Results:

• The proposed method is free from text-line detection and segmentation.
• It effectively exploits multiple visual cues beyond horizontal text-lines.
• Demonstrated robustness to various image degradations (distortion, blur, illumination) and complex layouts.
• Achieved strong performance on both synthetic and real-captured document images.

Conclusions:

• The slope field recovery method offers a robust and effective solution for curved baseline extraction.
• This approach significantly advances document image processing, particularly for challenging and distorted documents.
• The method's independence from text-line detection broadens its applicability across diverse document types and conditions.