Image Multi-Classification using PHOW Features

Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2016, Vol 18, Issue 5

Abstract

Abstract: Automatic labeling and classification of a vast number of images is a huge challenge, so machines are used as a part of image classification and annotation is turned into a prerequisite to adapt to the high improvement of advanced digital image innovations consistently. Scale Invariant Feature Transform (SIFT) is an image descriptor for image-based matching and recognition; this descriptor is used for computer vision purposes like point-matching between different views and object recognition in the same view. SIFT features are regarded as an efficient way for image classification due to its usefulness demonstration under real-world conditions. Also, representing these features in bag-of-words (BOW) model and spatial pyramid model adds the ability to distinguish spatial distribution to the former.

Authors and Affiliations

Shereen A. Hussein , HowidaYoussryAbd El Naby , Aliaa A. A. Youssif

Keywords

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  • EP ID EP149435
  • DOI -
  • Views 97
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How To Cite

Shereen A. Hussein, HowidaYoussryAbd El Naby, Aliaa A. A. Youssif (2016). Image Multi-Classification using PHOW Features. IOSR Journals (IOSR Journal of Computer Engineering), 18(5), 31-36. https://europub.co.uk/articles/-A-149435