CNN-BGRU-CTC

Urdu Katib Handwritten Dataset: Historical Urdu HTR benchmark with CRNN baseline evaluation

Researchers introduce the Urdu Katib Handwritten Dataset (UKHD), the first offline Urdu handwritten text lines dataset drawn from historical Katib (scribe) materials in the Nastalique calligraphic style. The paper evaluates several CRNN-based hybrid architectures for Urdu Handwritten Text Recognition, finding that a CNN-BGRU-CTC model achieves the best character and word error rates. The work addresses a recognized gap in cursive-script HTR research caused by the scarcity of benchmark datasets for Urdu.