Comparative Semantic Document Layout Analysis for Enhanced Document Image Retrieval

Tons of handwritten document images, either historical or continuously reproduced in everyday life, are information-rich, awaiting extensive advanced technological attention from academic and industrial communities. Document layout analysis (DLA) is a primary key that opens many doors for further sophisticated document image processing and understanding. It has been a primary interest of massive research on various domains, including document image retrieval (DIR), whereas little attention was paid to valuable semantic aspects. Recently, semantic DLA (SDLA) emerged to enable semantic information derivation and more invariant characterization. The viability of comparative-based SDLA for inferring comparative semantic characteristics has yet to be investigated. In this research, new comparative characteristics are proposed to empower more perceptive SDLA and improve retrieval capabilities. The proposed Comparative-SDLA not only utilizes the latent potency of semanticity in effectively characterizing handwritten document image layout but also exploits the power of comparability between relative semantic characteristics for further robust and enhanced DIR. A novel methodology framework is thoroughly described, implicating pairwise comparative-based automatic image annotation, document ranking by comparative characteristic, and comparative feature extraction. Several retrieval experiments on a sizable complex handwritten document dataset are conducted with extended performance evaluation, analysis, and comparison for comparative-based methods against non-comparative counterparts, highlighting promising capabilities to extend for other practical applications.