Thumbnail Image

Theses

Browse

20183
Reset filters
Subject: Information Technology × End date: 2018 × Start date: 2018 × Type: Thesis × Thesis Type: M.Tech. ×
Reset filters

Search Results

Now showing 1 - 3 of 3
  • Thumbnail Image
    ThesisItemOpen Access
    Analysis of Satellite Images using Support Vector Machine (SVM)
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2018-08) Arya, Diksha; Singh, Rajesh
    Satellite captured images are eyes in the sky that contain information from around the globe. The information derived from the Satellite Images is helpful in Remote Sensing Applications, Research and Analysis, Organizations or Government bodies in monitoring space, Civil defence operations, etc. Satellites captures huge collection of images at a regular interval of time and analyzing those images manually is very difficult and time consuming. Therefore, an ideal picture classifier system is required to be located that intend to classify the images captured from the satellites so that the images of interest can be easily retrieved. Thus, in our research we aimed to propose a Satellite Image Classification system that can automatically classify the category of physical scene present in an image. For achieving our objective we have utilized Support Vector Machine (SVM), a supervised machine learning algorithm for performing classification; two widely used techniques for extracting Features which are Grey Level Co-occurrence Matrix (GLCM) and Gabor Filter; and Fuzzy C Means for Image Segmentation. We have performed Satellite Image Classification for five physical categories namely Desert, Mountain, Residential, River and Forest. We measured our classification system accuracy using confusion metrics and calculated the precision, sensitivity, specificity and F1 Score. Our classification system achieved overall accuracy of 91.66%.
  • Thumbnail Image
    ThesisItemOpen Access
    A novel chaotic based keyless encryption technique for secured transmission of images
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2018-08) Singh, Chetana; Pandey, Binay Kumar
    These days secured data storage and transmission have become an important issue in this digital world due to increased use of internet for communication purpose. Information security is becoming more important as the amount of sensitivity data being exchanged on the Internet increases. The service like confidentiality and data integrity are required to protect data against unauthorized usage and modification. In these years several image encryption methods are introduced by various researches to secure multimedia information while transmit via public networks. A novel Keyless Image encryption method based on chaotic map is suggested in this research work. Each component of image is encrypted by shuffling pixels and this shuffling is decided by the modified cat map. To transmit data whole image is convert into linear form then modulate the linear data using modulation technique OQPSK. The results confirm that the proposed method resist the statistical analysis. Also attains acceptable correlation coefficient value and has a robust performance against attacks. The simulation of the above algorithm is done on Matlab.
  • Thumbnail Image
    ThesisItemOpen Access
    Fuzzy based semantic clustering of news articles
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2018-10) Priyanka; Joshi, Sanjay
    Text mining is a process that uses data mining approaches to extract valuable information held in the hidden form in textual data. In this paper, a framework for fuzzy clustering of news articles is proposed. These news articles originate on different news portals on the web. The data sets are fetched from two different Indian news portals, The Hindu archive and Times Of India archive. Six data sets are used for implementation and evaluation: 4 news articles Times of India, 150 news articles Times of India, 1000 news articles Times of India, 4 news articles The Hindu, 150 news articles The Hindu, 1000 news articles The Hindu. The fetched data is stored in a central database and then preprocessing reduces the noise. Tokenization is done to split the text content into separate words. Stop words are removed from the text data as they have no significance for cluster discrimination. Then lemmatization technique is applied. Tf-idf is calculated for the data set and saved in the word frequency vector. On these vectors, distance measure or similarity measure function is used to find the similarity between articles. Tf-idf with cosine similarity measure gives semantic similarity between articles. One article may belong to more than one cluster so fuzzy membership values must be generated. The articles are clustered using two clustering algorithms k-means clustering and fuzzy c-means clustering. The similar documents are grouped into same cluster and dissimilar documents are put into different clusters. The proposed framework shows that fuzzy clustering does not restrict each news article to belong exactly to one cluster. Therefore this framework when applied to information retrieval systems or other application systems, system gives better performance and relevance to the users.