Independent mobility (freedom to explore the environment without any accompaniment) reduces the dependence on caregivers. Disable people always find themselves challenging to go out independently because of their physical deficiency or inability to move in a normal fashion. A wheelchair is a mechanical device which improves the lifestyle and increase the mobility of disable people, allowing them to explore their surroundings. In this paper, we propose a new technique to control the powered/motorized wheelchair using Infrared Radiation (IR). An attempt has been provided to transmit low intensity infrared rays on eyes. The analog voltage level varies in infrared receiver based on eye lid movement. These techniques grant the user to navigate automatically to desired goal point with the possibility of avoiding collisions and holes in all directions, so that the user can robustly interact with the wheelchair. Main aim of this project is to reduce the human efforts in driving a wheelchair. The user with any extent of disability can operate the wheelchair to attain self-independence at least in daily life activities. The objective of this paper is to provide our services to the disable society by increasing their range of mobility.
Image registration is one of the challenging tasks in medical image analysis. While coming to non rigid image registration there are mainly two issues to consider. They are i) intensity similarity and ii) gray level transformation. The issue with intensity similarity is it is not necessarily equivalent to anatomical similarity when the anatomical correspondences between source and target images are established. Another issue is choosing an appropriate registration algorithm. It should be robust against monotonic gray-level transformation when aligning anatomical structures in the presence of bias fields. Here new feature- intensity based registration method developed for nonrigid brain image registration to overcome the above stated issues named as Anatomical Region Descriptor (ARD). This method is developed on image feature, it encodes geometric properties of anatomical structures and pixel wise interaction details. It is efficient and theoretically monotonic gray level transformation invariant. This method is integrated with intensity based registration algorithm named as residual complexity for Registration purpose. This proposed method is compared with three other non rigid image registration algorithms. Experimental results of the proposed method show that it achieves the highest accuracy rate among the compared methods.
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