Content‐based image retrieval system via sparse representation
The aim of image retrieval systems is to automatically assess, retrieve and represent relative images‐based user demand. However, the accuracy and speed of image retrieval are still an interesting topic of many researches. In this study, a new method based on sparse representation and iterative disc...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2016-02-01
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| Series: | IET Computer Vision |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/iet-cvi.2015.0165 |
| _version_ | 1797684925209509888 |
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| author | Sajad Mohamadzadeh Hassan Farsi |
| author_facet | Sajad Mohamadzadeh Hassan Farsi |
| author_sort | Sajad Mohamadzadeh |
| collection | DOAJ |
| description | The aim of image retrieval systems is to automatically assess, retrieve and represent relative images‐based user demand. However, the accuracy and speed of image retrieval are still an interesting topic of many researches. In this study, a new method based on sparse representation and iterative discrete wavelet transform has been proposed. To evaluate the applicability of the proposed feature‐based sparse representation for image retrieval technique, the precision at percent recall and average normalised modified retrieval rank are used as quantitative metrics to compare different methods. The experimental results show that the proposed method provides better performance in comparison with other methods. |
| first_indexed | 2024-03-12T00:36:52Z |
| format | Article |
| id | doaj.art-126518e08016486d8d8020b1a420f8dd |
| institution | Directory Open Access Journal |
| issn | 1751-9632 1751-9640 |
| language | English |
| last_indexed | 2024-03-12T00:36:52Z |
| publishDate | 2016-02-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Computer Vision |
| spelling | doaj.art-126518e08016486d8d8020b1a420f8dd2023-09-15T09:27:15ZengWileyIET Computer Vision1751-96321751-96402016-02-011019510210.1049/iet-cvi.2015.0165Content‐based image retrieval system via sparse representationSajad Mohamadzadeh0Hassan Farsi1Department of Electronics and Communications EngineeringUniversity of BirjandBirjandIranDepartment of Electronics and Communications EngineeringUniversity of BirjandBirjandIranThe aim of image retrieval systems is to automatically assess, retrieve and represent relative images‐based user demand. However, the accuracy and speed of image retrieval are still an interesting topic of many researches. In this study, a new method based on sparse representation and iterative discrete wavelet transform has been proposed. To evaluate the applicability of the proposed feature‐based sparse representation for image retrieval technique, the precision at percent recall and average normalised modified retrieval rank are used as quantitative metrics to compare different methods. The experimental results show that the proposed method provides better performance in comparison with other methods.https://doi.org/10.1049/iet-cvi.2015.0165content based image retrieval systemsparse representationimage based user demanditerative discrete wavelet transformfeature based sparse representationimage retrieval technique |
| spellingShingle | Sajad Mohamadzadeh Hassan Farsi Content‐based image retrieval system via sparse representation IET Computer Vision content based image retrieval system sparse representation image based user demand iterative discrete wavelet transform feature based sparse representation image retrieval technique |
| title | Content‐based image retrieval system via sparse representation |
| title_full | Content‐based image retrieval system via sparse representation |
| title_fullStr | Content‐based image retrieval system via sparse representation |
| title_full_unstemmed | Content‐based image retrieval system via sparse representation |
| title_short | Content‐based image retrieval system via sparse representation |
| title_sort | content based image retrieval system via sparse representation |
| topic | content based image retrieval system sparse representation image based user demand iterative discrete wavelet transform feature based sparse representation image retrieval technique |
| url | https://doi.org/10.1049/iet-cvi.2015.0165 |
| work_keys_str_mv | AT sajadmohamadzadeh contentbasedimageretrievalsystemviasparserepresentation AT hassanfarsi contentbasedimageretrievalsystemviasparserepresentation |