• Dr.Santosh Singh
• Sherlyn kevin
• Sanket Govind Sonawane
• Shiba Ibrahim shaikh

Because handwriting recognition is used so frequently in document analysis, biometrics, and other forensics fields, it has earned a lot of notoriety. Therefore, this project entails through investigation and the development of an advanced image processing system for handwriting detection. Therefore, the suggested method begins with the preprocessing steps, which comprise picture acquisition, noise reduction, and image enhancement, to produce better-quality photos. Subsequently, diverse methodologies such as texture analysis, contouring function, and intensity pixel histograms are utilized to distinguish specific attributes of handwritten designs from others. After that, the features are further categorized into different kinds of handwritings using classification techniques like decision trees and convolutional neural networks (CNN), among others. Scalability problems are then addressed, if applicable.

TensorFlow, Image processing, Convolutional Neural Network, Handwritten Recognition.

"Handwriting Detection System Using Image Processing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.d488-d490, April-2024, Available :http://www.jetir.org/papers/JETIR2404365.pdf

"Handwriting Detection System Using Image Processing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. ppd488-d490, April-2024, Available at : http://www.jetir.org/papers/JETIR2404365.pdf