Central Tendency Measurement based Unidentified Object Recognition System

At present era, Object recognition has become one of the most momentous tasks for various applications. The existing approach provides poor and inefficiency result due to complex behavior of real images, object size and shape. For object classification it is very important to extract the exact images from a given dataset. In this case, in many studies we have seen that object recognition has done tremendous representation. We envision a new approach of object recognition based on Mean, Median, Mode, Geometric mean, and standard deviation features using Euclidean distance. The overall goal of my research is to find a robust model for object recognition. The model will be robust in both time and accuracy. The experimental results show that this system can perform comparable recognition of object using these features and the evaluation results conclude that the proposed object recognition system shows better results than many existing methods. Keywords—Object recognition; Central tendency; Standard Deviation; Euclidean distance