Computer Vision, Pattern Recognition,Embedded Systems, Robotics, Machine Learning
Programming Languages: Python,C, C++, Matlab
With the advent of computer vision, every system seems to encompass the ideas and control system is not an exception to it. The notion of image processing articulates the ideas of intuitiveness and elegance in almost every engineering paradigm and ameliorates the systems which currently lag behinds in achieving fidelity that every systems is supposed to have. We propose here an image processing based ball and beam system, where the real time position sensing is carried out with a camera and PID control system has been attuned to overcome time and space instabilities. Our system has proven to work efficiently exhibiting a good dynamic response and thus has been a step towards novel inception in the domain of control system and computer vision based co-design.
This paper proposes a method to recognize static hand gestures in an image or video where a person is performing Nepali Sign Language (NSL) and translate it to words and sentences. The classification is carried out using Neural Network where contour of the hand is used as the feature. The work is verified successfully for NSL recognition using signer dependency analysis.