Comparative Study of Supervised Classification Algorithms for WOSRAS

A Wireless Object Sorting Robot Arm System (WOSRAS) is the combination of Machine Vision System (MVS), Wireless Embedded System (WES) and Robot Arm System (RAS). MVS is the essential fragment of the object sorting robot arm system which constitutes of an image sensor and LabVIEW installed personal computer system to classify the object from an image. NI vision acquisition express of LabVIEW acquires an image from the image sensor to identify the object in the image. The present work gives the intensive study of classification algorithms and the distance metrics. Each classification algorithm with its distance metric is evaluated to generate a classifier file. The performance of the classification algorithmsare compared to choose the best for object classification of image. NN (Nearest Neighbor), k-NN and Minimum Mean Distance (MMD) algorithms were considered for comparison. All the methods are analysed and compared for best results and maximum accuracy to implement in WOSRAS.