• KAVITA PATEL
• SACHIN HARNE

Vehicle Number Plate Identification (VNPI) is a part of digital image processing which is generally used in vehicle transportation system to categorize the vehicle. Number plate recognition systems are having varieties of application such as traffic maintenances, tracing stolen cars, automatic electronic Toll collection system etc. Foggy image detection and estimation assist the field of computer vision with auto-focussing technique and quality assessment of the image. This has unlocked the field of Foggy image detection, Foggy image estimation and de-fogging of the images. Foggy image is defined as the phase of image where its content turns out to be difficult to read and understand. The image may become Foggy image owing to limited contrast, untimely exposure, improper lighting environment and indecorous device handling. The proposed work contributes a study on to remove the noise of the image which may hinder the process of Foggy image detection. To identify the optimal threshold value which form the basis of the foggy image detection? To classify the images into foggy image and not foggy image images based on the identified threshold value. A certain amount of difficulties to license plate recognition are caused by the environment of rain and fog. License plate recognition system for this kind of environment is studied in this paper, based on the theory of digital image processing, computer vision and pattern recognition technology.

Foggy image, Vehicle number placete, Identification, Image clearance

"A Review on Foggy Image Clearance and Vehicle Number Plate Identification using Python", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 7, page no.1473-1476, July-2020, Available :http://www.jetir.org/papers/JETIR2007181.pdf

"A Review on Foggy Image Clearance and Vehicle Number Plate Identification using Python", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 7, page no. pp1473-1476, July-2020, Available at : http://www.jetir.org/papers/JETIR2007181.pdf