Identity document image analysis using artificial intelligence techniques

Identity document understanding is one of the most important parts in the document recognition systems, even though that many researches are done in "document image analysis", however this research still has many challenges. This research aims to find a better solution to analyse the identity document image using artificial intelligence techniques. Hence, proposed method detects the location of the important information in the identity document, classifies the text to many categories (date of birth, last name, first name...etc.), and detects the key objects in the identity document image like the face photo and signature and even the logos. Methods used in this research are divivded into two categories which are document type based and machine-readable zone (MRZ) based approaches. In the document type based method, first the document image is classified, then pre-trained model for each class is utilized to derive the information needed such as location and text segments for that class on the query image. In the MRZ based approach, first MRZ location is detected, then Visual Inspection Zone (VIZ) area zone with the MRZ information are matched and small Natural Language Processing (NLP) engine is utilized to detect text. The accuracy of the research was 94.8% with accurate detection for all segments in the document, and 3% with good detection. However some information in the document image was missing, resulting in 1% of wrong detection as false positive, and the last 3 was not detected at all. Consequently, the overall accuracy of the research was 97.8% of the test samples.