Newspaper Column Detection via Fourier Analysis
The Challenge
Their OCR software couldn’t understand the complex, irregular layouts of historical newspapers. This caused jumbled text output, forcing staff to manually correct 40% of all pages—a massive bottleneck in their digitization pipeline.
Our Solution
Applied 2D Fourier transforms to analyze the spatial frequency of text regions, identifying dominant columnar structures even in noisy or distorted scans. Combined with a CNN-based layout classifier and adaptive thresholding to handle varying column widths. Implemented post-processing with graph-based optimization.
Results & Impact
Achieved 92% column detection accuracy on complex layouts
Reduced OCR segmentation errors by 35%
Eliminated manual column corrections for 95% of pages
Enabled automated processing of 500K+ newspaper pages monthly
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