Multiclassifiers system for handwritten Arabic literal amounts recognition based on enhanced feature extraction model

Azzeddine, Menasria; Bennia, Abdelhak; Nemissi, Mohamed; Sedraoui, Moussa

doi:10.1117/1.jei.27.3.033024

Cited by 5 publications

(1 citation statement)

References 31 publications

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“…Automatic check processing involves several important modules, such as courtesy amount recognition (e.g., [18][19][20]), literal amount recognition (e.g., [21][22][23][24][25]), date verification (e.g., [26,27]), and signature verification (e.g., [13,28]) in addition to tasks such as recognizing check numbers and account numbers. Interested readers can refer to [29] for an old but relevant survey on Arabic check processing and to [14] for automatic check processing, in general.…”

Section: Related Workmentioning

confidence: 99%

A Hybrid Rule-Based and Machine Learning System for Arabic Check Courtesy Amount Recognition

Ahmad

2023

Sensors

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Courtesy amount recognition from bank checks is an important application of pattern recognition. Although much progress has been made on isolated digit recognition for Indian digits, there is no work reported in the literature on courtesy amount recognition for Arabic checks using Indian digits. Arabic check courtesy amount recognition comes with its own unique challenges that are not seen in isolated digit recognition tasks and, accordingly, need specific approaches to deal with them. This paper presents an end-to-end system for courtesy amount recognition starting from check images as input to recognizing amounts as a sequence of digits. The system is a hybrid system, combining rule-based modules as well as machine learning modules. For the amount recognition system, both segmentation-based and segmentation-free approaches were investigated and compared. We evaluated our system on the CENPARMI dataset of real bank checks in Arabic. We achieve 67.4% accuracy at the amount level and 87.15% accuracy at the digit level on the test set consisting of 626 check images. The results are presented with detailed analysis, and some possible future work is identified. This work can be used as a baseline to benchmark future research in Arabic check courtesy amount recognition.

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