• Tarun
• Rajni

The License Plate Character Recognition (LPCR) system is the most popular method for the mass surveillance of the automobiles nowadays. The LPCR system basically works into four steps first step is to preprocess the license plate and after that detection of the license plate is done and then extraction of numbers from that license plate is done and the four-step is character recognition which means to read out the characters of a number plate. The LPCR also some face some difficulties due to no uniform structure of number plates and illumination. The techniques developed until are mostly relied on some fixed parameters like a fixed image capturing angle and proper illumination and stationary background condition. These all techniques are varied on different factors like the processing time for a license number plate, the power consumption, its accuracy and error-free results. This LPCR system gives new vision in the intelligent transport system which opens a new way for the automobile industry towards an intelligent automobile world. Still being there are many types of research that are been carried out to develop the LPCR technique in terms of process complications. In this paper, comparison of KNN with different distance functions such as Manhattan, Spearman, Cosine, Minkowski, Euclidean is done in terms of average execution time, sample-wise execution time and recognition accuracy.

Offline Character Recognition, OCR, LPF, Classifier, License Plate Recognition, License Plate Character Recognition, Features Extraction; Survey, Plate Extraction, Character Segmentation

"License Plate Character Recognition Using Modified KNN", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 6, page no.10-15, June-2018, Available :http://www.jetir.org/papers/JETIR1806502.pdf

"License Plate Character Recognition Using Modified KNN", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 6, page no. pp10-15, June-2018, Available at : http://www.jetir.org/papers/JETIR1806502.pdf