A Hybrid Fake Banknote Detection Model using OCR, Face Recognition and Hough Feature
Authors: Shital S. Aher, Bachhav Prerana Sudam, Gunjal Vaishnavi Ashok, Dhone Vaibhav Shivaji, Yewale Mayur Sakhahari
Country: India
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Abstract: In this paper, the programmed framework is intended for ID of Indian cash notes and check whether it is phony or unique. The programmed framework is extremely valuable in banking framework and other field too. In India expansion in the fake money notes of 100, 500 and 1000 rupees. As expansion in the innovation like filtering, variety printing and copying due to that there is expansion in fake issue. In this paper, acknowledgment of phony Indian cash notes is finished by utilizing picture handling method. In this paper, acknowledgment of phony Indian money notes is finished by utilizing picture handling strategy. In this strategy first the picture obtaining is finished and applies preprocessing to the picture. In pre-handling harvest, smooth and change then, at that point, convert the picture into dim variety after change apply the picture division then, at that point, separate elements and diminish, at last looking at picture.
Keywords: Fake Currency, Counterfeit Detection, Image Processing, Feature Extraction
Paper Id: 230146
Published On: 2023-05-19
Published In: Volume 11, Issue 3, May-June 2023
Cite This: A Hybrid Fake Banknote Detection Model using OCR, Face Recognition and Hough Feature - Shital S. Aher, Bachhav Prerana Sudam, Gunjal Vaishnavi Ashok, Dhone Vaibhav Shivaji, Yewale Mayur Sakhahari - IJIRMPS Volume 11, Issue 3, May-June 2023.