Contour tracking based knowledge extraction and object recognition using deep learning neural networks

Object recognition in digital images are carried out using syntactic or spectral domain pattern recognition techniques. Due to ever increasing size of data collected by digital image acquisition systems there is a need to go in for developing faster, reliable and intelligent pattern recognition methods which would mostly supplement human intelligence in recognizing objects which otherwise remain latent and unnoticed. One such effort is use of deep learning neural networks for object recognition. The input to this system is knowledge extracted from the contours of various objects pre valent in a digital image. This paper advocates a novel method for extracting knowledge about the contours of various objects and components in a digital image and for recognizing objects using a neural network.