# Visual Script and Language Identification

arXiv: https://arxiv.org/abs/1601.01885 · HTML: https://mlsanity.com/paper/1601.01885/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Jan 2016.

## Built on by (most cited first, 3 of 3)

- [Structured Analysis and Comparison of Alphabets in Historical Handwritten Ciphers](https://mlsanity.com/paper/2410.21913/) (2024)
- [On-Device Spatial Attention based Sequence Learning Approach for Scene Text Script Identification](https://mlsanity.com/paper/2112.00448/) (2021)
- [TextileNet: Towards Zero-shot Text-style Segmentation of Manuscripts](https://mlsanity.com/paper/2607.09299/) (2026)

## Abstract (arXiv)

In this paper we introduce a script identification method based on hand-crafted texture features and an artificial neural network. The proposed pipeline achieves near state-of-the-art performance for script identification of video-text and state-of-the-art performance on visual language identification of handwritten text. More than using the deep network as a classifier, the use of its intermediary activations as a learned metric demonstrates remarkable results and allows the use of discriminative models on unknown classes. Comparative experiments in video-text and text in the wild datasets provide insights on the internals of the proposed deep network.