Handwriting Variation In Urdu And English Language Using Cnn - et. al., siddiqui Mohd. Khaja Moinuddin, (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
Handwriting Recognition Is The Automatic Transcription Of Handwriting, Where Only The Image Of The Handwriting Is Available. Manual Matching Shall Be Used By Banks For The Authentication Of Checks And Signatures. In Forensics, Handwriting Corresponding Algorithms Can Help Handwriting Analysts To Predict The Author With Greater Precision. This Handwriting Needs To Be Scanned To The Computer For The Handwriting Recognition System To Access It And Analyze It Consequently. A Variety Of Handwriting Applications, Including Transcription Papers, Mail Routing, And Processor Forms, Checks, And Faxes, May Be Envisaged. Several Applications Are Also Possible. The Extensive Research Effort Concentrated On The Field Of Character Recognition (Cr), Due Both To Its Possible Applications And To The Difficulties Involved In Simulating Human Reading. The New Offline Handwritten Recognition (Ohr) Is Designed For Both Urdu And English. It Mainly Focuses On The Removal Of Noises In Word, Character Segmentation Methods With Higher Recognition Rate. The Images Which Are Scanned May Contain Noises And Image Denoising Steps Consist Of Binarization, Noise Elimination, And Size Normalization. Words And Character Segmentation Are Performed By Using Particle Swarm Optimization (Pso) Algorithm. Then Those Segmented Samples Are Used For The Next Step Which Is Feature Extraction. Finally, Word Recognition Is Performed By Using The Deep Neural Network Classifier.