Thai–English Multiscript Text Image (TEMS) Dataset for Multiscript Image-Based Text Recognition

Publicly available datasets containing Thai and English scene text captured under unconstrained real-world conditions remain limited, particularly for multilingual and mixed-script text recognition. To address this gap, the Thai–English Multiscript Text Image (TEMS) Dataset was developed as a publicly available resource for multilingual scene text recognition research. Natural scene photographs containing Thai and English textual content were collected using smartphone cameras from diverse environments, including billboards, commercial storefronts, road signs, menus, packaging, and publication covers. Text regions were manually identified, verified, and extracted to generate cropped text images with corresponding transcription labels. The resulting dataset comprises 5000 text images derived from 1625 natural scene photographs and contains Thai text, English text, mixed Thai–English text, numerals, punctuation marks, and special symbols spanning 161 unique character classes. The dataset exhibits substantial variation in text length, image dimensions, font style, text size, illumination conditions, spatial arrangement, and background complexity. Statistical analysis indicates an average text length of 15.8 characters per image. In addition, image widths range from 45 to 1512 pixels and image heights range from 18 to 275 pixels. The TEMS Dataset provides a publicly available multilingual scene text resource for optical character recognition, scene text recognition, document understanding, computer vision, pattern recognition, and multilingual artificial intelligence research.