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  •   Nellutla Sasikala

  •   V. Swathipriya

  •   M. Ashwini

  •   V. Preethi

  •   A. Pranavi

  •   M. Ranjith

Abstract

This paper deals with image processing and feature extraction. Feature extraction plays a vital role in the field of image processing. There exist different image pre-processing approaches for feature extraction such as binarization, thresholding, resizing, normalisation so on...Then after these techniques are applied to obtain high clarity images. In Feature extraction object recognition and stereo matching are at the base of many computer vision problems. The descriptor generator module is changed for increasing the performance of algorithm. SIFT algorithm consist of two modules such as key point detection module and descriptor generation module. When compared to recent solution, the descriptor generation module speed is fifteen times faster and the time for feature extraction is also reduced.

Keywords: SIFT (Scale invariant feature transform), SIFT HOG (Scale invariant feature transform histogram of oriented gradients), SURF (Speeded up robust features).

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How to Cite
[1]
Sasikala, N., Swathipriya, V., Ashwini, M., Preethi, V., Pranavi, A. and Ranjith, M. 2020. Feature Extraction of Real-Time Image Using SIFT Algorithm. European Journal of Electrical Engineering and Computer Science. 4, 3 (May 2020). DOI:https://doi.org/10.24018/ejece.2020.4.3.206.