TY  - JOUR
AU  - Murugesan, Gokul 
AU  - Vasudevan, Shriram K. 
AU  - Ramachandran, Sivaraman 
AU  - Vasudevan, Subashri 
AU  - Arumugam, Balachandran 
PY  - 2013
TI  - Vehicle Identification using Fuzzy Adaline Neural Network
JF  - Journal of Computer Science
VL  - 9
IS  - 6
DO  - 10.3844/jcssp.2013.757.762
UR  - https://thescipub.com/abstract/jcssp.2013.757.762
AB  - Video surveillance is an important aspect in today’s world, where a particular scene of area requires monitoring to avoid terrorist attacks and unauthorized entries. Vehicle recognition is an important area in object tracking and recognition. Objects may be of rigid or non-rigid in nature with varying velocity and have different features. Important features like shape, logo, color and texture are complex in nature. Hence there is a need of better algorithm for detecting and identifying the objects like car. A new method is proposed for recognizing the cars present in the video. At first the features like shape is extracted using moments, logo using the Scale Invariant Feature Transform (SIFT) and the RGB color values of the car body. Using these features the recognition is carried out to classify the type of car. Recognition of cars has range of application like, military surveillance, traffic management, autonomous navigation system, auto parking.