Vehicle identification using fuzzy adaline neural network | Science Publications

Journal of Computer Science

Subashri Vasudevan¹  Shriram K. Vasudevan¹  Sivaraman Ramachandran¹  Gokul Murugesan¹  Balachandran Arumugam¹ 

关键词: SIFT;    Feature Descriptors;    ADALINE;    Fuzzy;   

DOI  :  10.3844/jcssp.2013.757.762

学科分类：计算机科学（综合）

来源: Science Publications

【 摘 要 】

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.

【 授权许可】

Unknown