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Vehicles are becoming smarter by the combining of greater power to compute connectivity solutions and the improvement in software visions. In modern vehicles automotive designs are interfaced with these features. This particular design includes keyless entry system and immobilizer system as the main weapons to prevent the vehicle theft. But these type of systems provide or detect the unauthorized access of vehicles to a measurable limit only. These security frameworks have straightforward also, lacking nature. So car burglary has been a persevering issue far and wide and a greater test from the profficient criminals. This paper proposes an aim to design efficient security control for auto theft prevention system by adding notable enhancement features such as a fingerprint system, password and OTP generating system. It is also included with some rationalizing security features like GPS fencing, remote engine cut-off, and conveying location of vehicle as a message using GSM module. These features are implemented with the help of fingerprint recognition module, GPS Receiver, GSM cellular modem. Along with these feature accident detection module is also added.

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A New model is designed for boundary detection and applied it to object segmentation problem in medical images. Our edge following technique incorporates a vector image model and the edge map information. The proposed technique was applied to detect the object boundaries in several types of noisy images where the ill-defined edges were encountered. The proposed techniques performances on object segmentation and computation time were evaluated by comparing with the popular methods, i.e., the ACM, GVF snake models. Several synthetic noisy images were created and tested. The method is successfully tested in different types of medical images including aortas in cardiovascular MR images, and heart in CT images.