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Pregled bibliografske jedinice broj: 870365

Improving performance of content based image retrieval system with color features


Hladnik, Aleš; Poljičak, Ante
Improving performance of content based image retrieval system with color features // Acta graphica, 27 (2016), 4; 7-12 (podatak o recenziji nije dostupan, članak, znanstveni)


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Naslov
Improving performance of content based image retrieval system with color features

Autori
Hladnik, Aleš ; Poljičak, Ante

Izvornik
Acta graphica (0353-4707) 27 (2016), 4; 7-12

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
content based image retrieval ; texture features ; color features ; image database

Sažetak
Content based image retrieval (CBIR) encompasses a variety of techniques with a goal to solve the problem of searching for digital images in a large database by their visual content. Applications where the retrieval of similar images plays a crucial role include personal photo and art collections, medical imaging, multimedia publications and video surveillance. Main objective of our study was to try to improve the performance of the query-by-example image retrieval system based on texture features – Gabor wavelet and wavelet transform – by augmenting it with color information about the images, in particular color histogram, color autocorrelogram and color moments. Wang image database comprising 1000 natural color images grouped into 10 categories with 100 images was used for testing individual algorithms. Each image in the database served as a query image and the retrieval performance was evaluated by means of the precision and recall. e number of retrieved images ranged from 10 to 80. The best CBIR performance was obtained when implementing a combination of all 190 texture- and color features. Only slightly worse were the average precision and recall for the texture- and color histogram-based system. is result was somewhat surprising, since color histogram features provide no color spatial informa- tion. We observed a 23% increase in average precision when comparing the system containing a combination of texture- and all color features with the one consisting of exclusively texture descriptors when using Euclidean distance measure and 20 retrieved images. Addition of the color autocorrelogram features to the texture de- scriptors had virtually no e ect on the performance, while only minor improvement was detected when adding rst two color moments – the mean and the standard deviation. Similar to what was found in the previous studies with the same image database, average precision was very high in case of dinosaurs and owers and very low with beach, food, monuments and mountains images.

Izvorni jezik
Engleski

Znanstvena područja
Grafička tehnologija, Računarstvo



POVEZANOST RADA


Ustanove:
Grafički fakultet, Zagreb

Profili:

Avatar Url Ante Poljičak (autor)

Citiraj ovu publikaciju:

Hladnik, Aleš; Poljičak, Ante
Improving performance of content based image retrieval system with color features // Acta graphica, 27 (2016), 4; 7-12 (podatak o recenziji nije dostupan, članak, znanstveni)
Hladnik, A. & Poljičak, A. (2016) Improving performance of content based image retrieval system with color features. Acta graphica, 27 (4), 7-12.
@article{article, author = {Hladnik, Ale\v{s} and Polji\v{c}ak, Ante}, year = {2016}, pages = {7-12}, keywords = {content based image retrieval, texture features, color features, image database}, journal = {Acta graphica}, volume = {27}, number = {4}, issn = {0353-4707}, title = {Improving performance of content based image retrieval system with color features}, keyword = {content based image retrieval, texture features, color features, image database} }
@article{article, author = {Hladnik, Ale\v{s} and Polji\v{c}ak, Ante}, year = {2016}, pages = {7-12}, keywords = {content based image retrieval, texture features, color features, image database}, journal = {Acta graphica}, volume = {27}, number = {4}, issn = {0353-4707}, title = {Improving performance of content based image retrieval system with color features}, keyword = {content based image retrieval, texture features, color features, image database} }

Uključenost u ostale bibliografske baze podataka::


  • Ecology Abstracts
  • DOAJ
  • EBSCO
  • I2OR
  • OAJI





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