dissertation · Brno University of Technology Digital Library (Brno University of Technology) · 2015

Image Database Query by Example

Dobrotka, Matúš

Cited by 0Abstract and details only

Abstract

This thesis deals with content-based image retrieval. The objective of the thesis is to develop an application, which will compare different approaches of image retrieval. First basic approach consists of keypoints detection, local features extraction and creating a visual vocabulary by clustering algorithm - k-means. Using this visual vocabulary is computed histogram of occurrence count of visual words - Bag of Words (BoW), which globally represents an image. After applying an appropriate metrics, it follows finding similar images. Second approach uses deep convolutional neural networks (DCNN) to extract feature vectors. These vectors are used to create a visual vocabulary, which is used to calculate BoW. Next procedure is then similar to the first approach. Third approach uses extracted vectors from DCNN as BoW vectors. It is followed by applying an appropriate metrics and finding similar images. The conclusion describes mentioned approaches, experiments and the final evaluation.

Cite this paper

APA 7

Dobrotka, M. (2015). Image Database Query by Example. Brno University of Technology Digital Library (Brno University of Technology).

MLA 9

Dobrotka, Matúš. “Image Database Query by Example.” Brno University of Technology Digital Library (Brno University of Technology), 2015.

Chicago

Dobrotka, Matúš. 2015. “Image Database Query by Example.” Brno University of Technology Digital Library (Brno University of Technology).

Harvard

Dobrotka, M. (2015) ‘Image Database Query by Example’, Brno University of Technology Digital Library (Brno University of Technology).

BibTeX

@phdthesis{dobrotka2015image,
  title = {{Image Database Query by Example}},
  author = {Dobrotka, Matúš},
  school = {Brno University of Technology Digital Library (Brno University of Technology)},
  year = {2015}
}

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