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arXiv Computer Vision By Ousmane Hamadou, Jean Louis Kedieng Ebongue Fendji

Frugal Handwritten Text Recognition for Sub-Saharan Civil-Status Registers: A Smartphone-to-Records Pipeline with CPU-Only Inference

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The paper presents a low‑resource pipeline for converting handwritten civil‑status registers in Sub‑Saharan Africa into searchable text using only a smartphone for capture and a laptop CPU for inference. It introduces a new corpus of 1,568 smartphone images from a Chadian municipal registry, and shows that a classical preprocessing stage plus a fine‑tuned Kraken recognizer can achieve a character error rate of 0.50% and a word error rate of 3.37% on a test set with writers seen during training. The recognizer is lightweight (61 MiB) and runs in under 6 s per image on a six‑core laptop, demonstrating that such a frugal system is feasible for local administrations lacking GPUs or reliable connectivity.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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