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Orthographic similarity is a measure of the degree of visual correspondence between two written text representations based on the arrangement, composition, and spatial configuration of their graphic symbols. Within handwritten text recognition and computer vision, the concept describes the extent to which character or word images share comparable visual patterns derived from stroke structures, symbol shapes, character layouts, and spatial relationships, independent of their semantic or linguistic meanings ^[1]. Orthographic similarity is typically characterized by the comparison of image-level or representation-level features, including contour information, pixel distributions, structural patterns, and geometric configurations extracted from handwritten or printed text samples ^[2]. It differs from semantic similarity, which concerns equivalence or relatedness of meaning, and from phonetic similarity, which concerns correspondence in sound patterns. In handwriting recognition systems, orthographic similarity represents a visual similarity relationship between textual forms that can be quantified through feature-based or learned similarity measures for comparing and analyzing written symbols and text images ^[3].