A Review On Offline Gujarati Word Categories Using Hybrid Features - Solanki, Amitkumar T; Degadwala, Sheshang D; Shekokar, Kishori (International Journal of Computer Sciences and Engineering, 2025)
The input to handheld devices using a traditional keyboard is not a user-friendly process for Indian scripts due to large and complex character sets. Handwritten character recognition can be a best possible solution. Handwritten character recognition is gaining noteworthy attention in the area of pattern matching and machine learning. Named categories Recognition is a method to find for a particular Named field from a file or an image, recognize it and classify it into specified Entity Classes like Name, Location, Organization, Numbers and Other Categories. The main purpose of using Hybrid Feature is that it provides better performance and can be easily implemented for any languages. A remarkable amount of work has been carried out for many languages like English, Greek, and Chinese etc. But still a wide scope is open for Indian Origin Languages like Hindi, Gujarati, and Devanagari etc. As Gujarati is not only the Indian Language, but a language that is most spoken in Gujarat. Thus, in this research paper different type of features and classification techniques are compare with advantages and disadvantages. After review all methods give idea for future direction research for Guajarati OCR recognition