Lexical Analyser for Automated Image Classification and Applying Classification on Google Earth
V. K. Panchal, Harish Kundra, Gaganpreet Singh · International Journal of Computer Applications · 2010
Rough Set based Optimization, Fuzzy Set Based Optimization, Biogeography Based Optimization Technique and many others like Classification based on many other Technologies of Soft Computing is the Research work going on in the DTRL LAB and has its application in various domain, so that we can use it in Remote Sensing for classification of satellite images. But all this Work already going on is found very Typical, A lot of Time Consuming and Quite Tiring, as the coding Process it Involves is quite Large and Complex. So we tried to mark the First Initial step towards the Automating of the Coding System and more to that using of the Coding through an Interactive GUI Based System which would evolve more inclination towards the work with less amount of Effort. So we Introduced an Automated Code generation System for Image Classification and for Developing its Complex Code we made a start with the most heavily used Technology of artificial Intelligence prevailing for classification process in the DTRL lab, that is the Rough Set Theory. Although in further stages of this project its aims to form the system for all technologies including Fuzzy and others. This work focuses on automating the coding of the optimized algorithm inspired by rough set technology for satellite image classification from high resolution satellite multi-spectral images. And further using the Classified Image in more efficient ways by embedding it on Google Earth, and making it global for use, and not merely global in use but even adding more prospects of functionality to it, with the powerful google earth system. This project will help for better programming of the classifier and efficient use of the classified image obtained from the satellite images after classification. In the future, the access to image archives will even become more difficult due to the enormous data quantity acquired by a new generation of high-resolution satellite sensors. To overcome such a challenge problem, new technologies those allow the users to access remote sensing images automatically is required. This work is a move to these technologies. The full text of the article is not available in the cache. Kindly refer the IJCA digital library at www.ijcaonline.org for the complete article. In case, you face problems while downloading the full-text, please send a mail to editor at [email protected]