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The implementation of an embedded system which is competent in detection of human body parts. In a catastrophe, for example, an avalanche or seismic tremor, and many other, where it is conceivable that the underlying state of threat holds on as would be the situation of a quake, in which inside a building bars and parts of the structure stay conferred, and in addition the general population who chance their lives discovering casualties. Another problem is that there is a large scale variation in those objects. Object detection and tracking algorithm must take place in near real time. In…mehr

Produktbeschreibung
The implementation of an embedded system which is competent in detection of human body parts. In a catastrophe, for example, an avalanche or seismic tremor, and many other, where it is conceivable that the underlying state of threat holds on as would be the situation of a quake, in which inside a building bars and parts of the structure stay conferred, and in addition the general population who chance their lives discovering casualties. Another problem is that there is a large scale variation in those objects. Object detection and tracking algorithm must take place in near real time. In response, the designed system implemented on a robot provides a solution by using artificial intelligence algorithms and image processing running on embedded systems. Using the object detection algorithm like Haar cascade classifier it detects the image of whole face, eyes, and mouth. The System, in our context, is a smaller version of an autonomous system. For example, autonomous systems could bemobile robots, miniature helicopter/quad rotor systems, or smart cars such a self-driving vehicles.By using algorithms that provide robust and efficient detection and tracking device.
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Autorenporträt
Malik Shahnawaz Khan is a post-graduation student in Electronics and Communication (Communication Systems Engineering) & Dr. Anilkumar Suthar is a Guide and Director of LJIET.