The main objective of this paper is to discuss a platform which can provide accurate
information to moving objects like a car in poor environmental conditions where the use of signals of GPS is not possible. This approach is going to integrate imaging sensor data into an inertial navigation system. Navigation systems are getting smart and accurate but still, an error occurs at long distances causing a failure to find out accurate location. In order to increase the accuracy front camera in a car is proposed as a sensor for the navigation system. Before this problem is solved with the help of extended Kalmanfilter but still, the small error occurs. In order to find out, accurate location landmarks will be detected from the real-time environment and will be matched with the landmarks which are already stored database. Detection is the challenge in an open environment in which object must be illumination invariant, pose invariant and scale invariant. Selection between algorithms according to the requirement is important. SIFT is a feature descriptor which creates the description of features in an image and known as the more accurate algorithm. Speeded up robust features (SURF) is another algorithm in computer considered as fast and less accurate than SIFT. Most of the time it is not a problem with given algorithms but the feature is not detected or matched because of illumination, scale, and pose. In this condition use of filters and other techniques is important for better results. Better results mean required information from images must extract easily, this part is obtained with the help of computer vision and image processing. After creating matched images data, this data is given to navigation data calculation so that it can produce an exact location based on matched images and time calculation. Navigation data calculation unit has the connection with Landmark Database so navigation system can compute that at this point landmark is present and it is matched and assure that given location is accurate. In this way accuracy, safety and security can be assured.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:31766 |
| Date | 24 September 2018 |
| Creators | Jumani, Kashif Rashid |
| Contributors | Hardt, Wolfram, Hardt, Wolfram, Nagler, Michael, Foerster, Thomas, Technische Universität Chemnitz |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/acceptedVersion, doc-type:masterThesis, info:eu-repo/semantics/masterThesis, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
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