The use of vehicles becomes important everywhere in the world with an increase in the use of vehicles. There has been a steady increase in accidents as well, vehicle manufacturers are attaining the security features of their products by introducing advanced automated technologies to
avoid accidents from occurring but no significant growth has been seen on technologies to implement proper measures to ensure the safety of a person after the accident has occurred. Our solution implements various layers of security measures to prevent an unauthorized person from using a vehicle
and at the same time creating a steady communication between accident victims and the emergency responders. Our device uses various sensors to analyze the data live and instantly create a communication between victim and responder which provides detailed information about the intensity of
the accident along with the GPS location to increase the possibility of survival in a dire situation.
The future holds the possibility of hospitals sharing medical images obtained through non-invasive systems to patients remotely. The advent of cloud and the storage and deployment of medical healthcare images in the cloud has resulted in the increased need for application of Cryptographic techniques to protect them from unauthorized access and malicious attacks. The Digital Imaging and Communication in Medicine (DICOM) standard is more compatible across medical imaging instruments globally. The pixel data of DICOM images requires more privacy and security. A novel ECDS based cryptographic approach is suggested to encrypt the original DICOM image as well as the ROI pixel data extracted from DICOM images. Results computed experimentally have proved that medical image encryption via ECDH is more robust, efficient and faster than existing medical image encryption schemes.
Medical Images cannot be utilized similarly it was procured. The obtained images must be Pre-Processed and Segmented. Real confinements are there in medical image preprocessing as far as multifaceted nature when contrasted with preparing different kinds of images. Confinements in image acquisitions make image division a repetitive procedure. The most significant objective of segmenting medical images is in performing activities on medical images for distinguishing designs and in recovering data. This survey speaks primarily about medical image handling. At that point many methods have been proposed to deal with portions of Medical images. The similar investigation of different processing procedures has been analysed. The overview thus gives subtleties of mechanized division strategies, explicitly talked about with regards to scanned medical images. The rationale is in analysing the issues experienced in dividing the scanned medical images, and the respective benefits and confinements techniques as of now accessible for segmentation of medical images.
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