Image Local Features Description Through Polynomial Approximation
<p dir="ltr">This work introduces a novel local patch descriptor that remains invariant under varying conditions of orientation, viewpoint, scale, and illumination. The proposed descriptor incorporate polynomials of various degrees to approximate the local patch within the image. Bef...
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| مؤلفون آخرون: | , , , , , |
| منشور في: |
2019
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| الموضوعات: | |
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إضافة وسم
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| _version_ | 1864513561178406912 |
|---|---|
| author | Fawad - (17018015) |
| author2 | Muhibur Rahman (16864351) Muhammad Jamil Khan (16864352) Muhammad Adeel Asghar (16864353) Yasar Amin (16864354) Salman Badnava (16864356) Seyed Sajad Mirjavadi (16864357) |
| author2_role | author author author author author author |
| author_facet | Fawad - (17018015) Muhibur Rahman (16864351) Muhammad Jamil Khan (16864352) Muhammad Adeel Asghar (16864353) Yasar Amin (16864354) Salman Badnava (16864356) Seyed Sajad Mirjavadi (16864357) |
| author_role | author |
| dc.creator.none.fl_str_mv | Fawad - (17018015) Muhibur Rahman (16864351) Muhammad Jamil Khan (16864352) Muhammad Adeel Asghar (16864353) Yasar Amin (16864354) Salman Badnava (16864356) Seyed Sajad Mirjavadi (16864357) |
| dc.date.none.fl_str_mv | 2019-12-13T00:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1109/ACCESS.2019.2959326 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Image_Local_Features_Description_Through_Polynomial_Approximation/24006804 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Information and computing sciences Applied computing Computer vision and multimedia computation Feature extraction Lighting Histograms Image edge detection Detectors Shape Image coding Covariant Descriptor Handcrafted feature Patch Textures |
| dc.title.none.fl_str_mv | Image Local Features Description Through Polynomial Approximation |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">This work introduces a novel local patch descriptor that remains invariant under varying conditions of orientation, viewpoint, scale, and illumination. The proposed descriptor incorporate polynomials of various degrees to approximate the local patch within the image. Before feature detection and approximation, the image micro-texture is eliminated through a guided image filter with the potential to preserve the edges of the objects. The rotation invariance is achieved by aligning the local patch around the Harris corner through the dominant orientation shift algorithm. Weighted threshold histogram equalization (WTHE) is employed to make the descriptor in-sensitive to illumination changes. The correlation coefficient is used instead of Euclidean distance to improve the matching accuracy. The proposed descriptor has been extensively evaluated on the Oxford’s affine covariant regions dataset, and absolute and transition tilt dataset. The experimental results show that our proposed descriptor can categorize the feature with more distinctiveness in comparison to state-of-the-art descriptors.</p><h2>Other Information</h2><p dir="ltr">Published in: Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0/legalcode" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="http://dx.doi.org/10.1109/access.2019.2959326" rel="noreferrer" target="_blank"><u>http://dx.doi.org/10.1109/access.2019.2959326</u></a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_97ab5b4bbcd227bd89aac6d86b5e97c0 |
| identifier_str_mv | 10.1109/ACCESS.2019.2959326 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/24006804 |
| publishDate | 2019 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Image Local Features Description Through Polynomial ApproximationFawad - (17018015)Muhibur Rahman (16864351)Muhammad Jamil Khan (16864352)Muhammad Adeel Asghar (16864353)Yasar Amin (16864354)Salman Badnava (16864356)Seyed Sajad Mirjavadi (16864357)Information and computing sciencesApplied computingComputer vision and multimedia computationFeature extractionLightingHistogramsImage edge detectionDetectorsShapeImage codingCovariantDescriptorHandcrafted featurePatchTextures<p dir="ltr">This work introduces a novel local patch descriptor that remains invariant under varying conditions of orientation, viewpoint, scale, and illumination. The proposed descriptor incorporate polynomials of various degrees to approximate the local patch within the image. Before feature detection and approximation, the image micro-texture is eliminated through a guided image filter with the potential to preserve the edges of the objects. The rotation invariance is achieved by aligning the local patch around the Harris corner through the dominant orientation shift algorithm. Weighted threshold histogram equalization (WTHE) is employed to make the descriptor in-sensitive to illumination changes. The correlation coefficient is used instead of Euclidean distance to improve the matching accuracy. The proposed descriptor has been extensively evaluated on the Oxford’s affine covariant regions dataset, and absolute and transition tilt dataset. The experimental results show that our proposed descriptor can categorize the feature with more distinctiveness in comparison to state-of-the-art descriptors.</p><h2>Other Information</h2><p dir="ltr">Published in: Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0/legalcode" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="http://dx.doi.org/10.1109/access.2019.2959326" rel="noreferrer" target="_blank"><u>http://dx.doi.org/10.1109/access.2019.2959326</u></a></p>2019-12-13T00:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1109/ACCESS.2019.2959326https://figshare.com/articles/journal_contribution/Image_Local_Features_Description_Through_Polynomial_Approximation/24006804CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/240068042019-12-13T00:00:00Z |
| spellingShingle | Image Local Features Description Through Polynomial Approximation Fawad - (17018015) Information and computing sciences Applied computing Computer vision and multimedia computation Feature extraction Lighting Histograms Image edge detection Detectors Shape Image coding Covariant Descriptor Handcrafted feature Patch Textures |
| status_str | publishedVersion |
| title | Image Local Features Description Through Polynomial Approximation |
| title_full | Image Local Features Description Through Polynomial Approximation |
| title_fullStr | Image Local Features Description Through Polynomial Approximation |
| title_full_unstemmed | Image Local Features Description Through Polynomial Approximation |
| title_short | Image Local Features Description Through Polynomial Approximation |
| title_sort | Image Local Features Description Through Polynomial Approximation |
| topic | Information and computing sciences Applied computing Computer vision and multimedia computation Feature extraction Lighting Histograms Image edge detection Detectors Shape Image coding Covariant Descriptor Handcrafted feature Patch Textures |