Improvement of CRF-Based Saliency Detection Algorithm Using Matrix Decomposition Based Features
One of the most important processing steps in the human vision system is the detection of a scene saliency map. Since saliency map can be applied to algorithms such as segmentation, compression and image retrieval, Researchers have focused on providing an efficient model to recognize it. Although a...
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| Format: | Article |
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University of Qom
2020-09-01
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| Series: | مدیریت مهندسی و رایانش نرم |
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| Online Access: | https://jemsc.qom.ac.ir/article_1275_1f6cd23b3430eaba3d8b821d80f59dba.pdf |
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| author | Mohammad Shouryabi Mohammad Javad Fadaeieslam |
| author_facet | Mohammad Shouryabi Mohammad Javad Fadaeieslam |
| author_sort | Mohammad Shouryabi |
| collection | DOAJ |
| description | One of the most important processing steps in the human vision system is the detection of a scene saliency map. Since saliency map can be applied to algorithms such as segmentation, compression and image retrieval, Researchers have focused on providing an efficient model to recognize it. Although a lot of works have been done in this area, the obtained saliency maps are still not satisfying enough. For this purpose, we propose a simple and supervised algorithm to identify the saliency map using a conditional random field (CRF) and saliency cues. In the proposed method, local contrast, center-bias, and backgroundness features have been used for CRF training. Additionally, a new feature based on matrix decomposition has been employed to improve the performance. In the following, CRF has been trained according to the features of 20 images close to the input image. Finally, input image saliency is estimated according to calculated weights in the training phase, input image saliency cues, and ground truths. The proposed method outperforms other methods in terms of algorithm implementation accuracy and speed. |
| format | Article |
| id | doaj-art-0fdc09b8ae704bd79e7ab6c3e9432ed6 |
| institution | Kabale University |
| issn | 2538-6239 2538-2675 |
| language | fas |
| publishDate | 2020-09-01 |
| publisher | University of Qom |
| record_format | Article |
| series | مدیریت مهندسی و رایانش نرم |
| spelling | doaj-art-0fdc09b8ae704bd79e7ab6c3e9432ed62025-01-30T20:17:44ZfasUniversity of Qomمدیریت مهندسی و رایانش نرم2538-62392538-26752020-09-016215116610.22091/jemsc.2018.12751275Improvement of CRF-Based Saliency Detection Algorithm Using Matrix Decomposition Based FeaturesMohammad Shouryabi0Mohammad Javad Fadaeieslam1Electrical and Computer Engineering Faculty, Semnan University,Semnan, IranElectrical and Computer Engineering Department, Semnan University Semnan, IranOne of the most important processing steps in the human vision system is the detection of a scene saliency map. Since saliency map can be applied to algorithms such as segmentation, compression and image retrieval, Researchers have focused on providing an efficient model to recognize it. Although a lot of works have been done in this area, the obtained saliency maps are still not satisfying enough. For this purpose, we propose a simple and supervised algorithm to identify the saliency map using a conditional random field (CRF) and saliency cues. In the proposed method, local contrast, center-bias, and backgroundness features have been used for CRF training. Additionally, a new feature based on matrix decomposition has been employed to improve the performance. In the following, CRF has been trained according to the features of 20 images close to the input image. Finally, input image saliency is estimated according to calculated weights in the training phase, input image saliency cues, and ground truths. The proposed method outperforms other methods in terms of algorithm implementation accuracy and speed.https://jemsc.qom.ac.ir/article_1275_1f6cd23b3430eaba3d8b821d80f59dba.pdfdetection of a scene saliencyconditional random fieldmatrix decomposition |
| spellingShingle | Mohammad Shouryabi Mohammad Javad Fadaeieslam Improvement of CRF-Based Saliency Detection Algorithm Using Matrix Decomposition Based Features مدیریت مهندسی و رایانش نرم detection of a scene saliency conditional random field matrix decomposition |
| title | Improvement of CRF-Based Saliency Detection Algorithm Using Matrix Decomposition Based Features |
| title_full | Improvement of CRF-Based Saliency Detection Algorithm Using Matrix Decomposition Based Features |
| title_fullStr | Improvement of CRF-Based Saliency Detection Algorithm Using Matrix Decomposition Based Features |
| title_full_unstemmed | Improvement of CRF-Based Saliency Detection Algorithm Using Matrix Decomposition Based Features |
| title_short | Improvement of CRF-Based Saliency Detection Algorithm Using Matrix Decomposition Based Features |
| title_sort | improvement of crf based saliency detection algorithm using matrix decomposition based features |
| topic | detection of a scene saliency conditional random field matrix decomposition |
| url | https://jemsc.qom.ac.ir/article_1275_1f6cd23b3430eaba3d8b821d80f59dba.pdf |
| work_keys_str_mv | AT mohammadshouryabi improvementofcrfbasedsaliencydetectionalgorithmusingmatrixdecompositionbasedfeatures AT mohammadjavadfadaeieslam improvementofcrfbasedsaliencydetectionalgorithmusingmatrixdecompositionbasedfeatures |