A novel approach recognizing objects from images by using SIFT and HMM
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Date
2018-08
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G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand)
Abstract
Recognizing Objects in images and finding a particular image from the set of images have always been a challenging task. There has been significant progress in this area as discussed in literature survey part of the thesis. This section proposed a novel approach for recognizing such objects by the use of algorithms SIFT and HMM which are used for the purpose of feature extraction and classification. The survey papers of last few years clearly shows that there has been a missing in the use of SIFT and HMM for recognizing the images. Therefore, The proposed framework will perform the recognition of an object as human or something by using database images and store the derived features or Keypoints from image sequence for measurement in recognition stage. An automated extraction of relevant feature point from given image is provided to automate the recognition procedure using SIFT. This process improves the recognition accuracy. The human facial features extracted through SIFT are utilized for the recognition of human. The SIFT feature will be created for each given images and the key points are computed, and then HMM is applied for recognition. HMM uses SIFT feature to perform recognition process on MATLAB. The recognition outcomes demonstrate that our proposed framework gives more accurate performance when comparing to tradition procedure.
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