SARCH: Multimodal Search for Archaeological Archives
Nivedita Sinha, Bharati Khanijo, Sanskar Singh, Priyansh Mahant, Ashutosh Roy, Saubhagya Singh Bhadouria, Arpan Jain, Maya Ramanath

TL;DR
This paper presents SARCH, a multimodal search system for archaeological archives that integrates text, images, and tables from scanned PDFs to improve retrieval effectiveness.
Contribution
It introduces a novel multi-modal search pipeline tailored for archaeological documents, combining multiple retrieval strategies for enhanced accuracy.
Findings
Hybrid retrieval approach outperforms single-modality methods
Effective extraction and classification of images from scanned PDFs
Preliminary results show promising retrieval performance
Abstract
In this paper, we describe a multi-modal search system designed to search old archaeological books and reports. This corpus is digitally available as scanned PDFs, but varies widely in the quality of scans. Our pipeline, designed for multi-modal archaeological documents, extracts and indexes text, images (classified into maps, photos, layouts, and others), and tables. We evaluated different retrieval strategies, including keyword-based search, embedding-based models, and a hybrid approach that selects optimal results from both modalities. We report and analyze our preliminary results and discuss future work in this exciting vertical.
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Taxonomy
TopicsAdvanced Image and Video Retrieval Techniques · Information Retrieval and Search Behavior · Handwritten Text Recognition Techniques
