Hybrid Multi-Phase Page Matching and Multi-Layer Diff Detection for Japanese Building Permit Document Review

arXiv cs.CL / 4/23/2026

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Key Points

The paper introduces a hybrid, multi-phase page matching algorithm to automatically align Japanese building permit PDF page sets across revision cycles where ordering and numbering may change.
It combines LCS-based structural alignment with a seven-phase consensus matching pipeline, followed by a dynamic-programming optimal alignment stage for robust page pairing.
A multi-layer diff engine is proposed to generate highlighted discrepancy reports using text-level, table-level, and pixel-level visual differencing.
On real-world permit documents, the method reports strong results (F1=0.80) with perfect precision (1.00) and zero false-positive matched page pairs on a manually annotated benchmark.
The approach targets labor-intensive and error-prone manual cross-referencing in Japan’s building permit review workflow.

Abstract

We present a hybrid multi-phase page matching algorithm for automated comparison of Japanese building permit document sets. Building permit review in Japan requires cross-referencing large PDF document sets across revision cycles, a process that is labor-intensive and error-prone when performed manually. The algorithm combines longest common subsequence (LCS) structural alignment, a seven-phase consensus matching pipeline, and a dynamic programming optimal alignment stage to robustly pair pages across revisions even when page order, numbering, or content changes substantially. A subsequent multi-layer diff engine -- comprising text-level, table-level, and pixel-level visual differencing -- produces highlighted difference reports. Evaluation on real-world permit document sets achieves F1=0.80 and precision=1.00 on a manually annotated ground-truth benchmark, with zero false-positive matched pairs.