A Spatially-Aware Search Engine for Textual Content in Images

Standard image search engines often treat text within images as secondary metadata or ignore its spatial location. This limits users' ability to find images based on text appearing in specific visual areas. We present a spatially-aware textual image search engine designed to address this limitation. Our approach utilizes an inverted index mapping text n-grams to their normalized bounding box coordinates within images. Queries consist of text and an optional spatial region. Relevance scoring combines spatial and textual factors using cosine similarity with n-gram length, weighted according to configurable parameters. To facilitate development and evaluation, we developed a pipeline for generating synthetic datasets with controlled text placement and ground truth.

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