Pub Date : 2014-12-01DOI: 10.1109/VCIP.2014.7051500
Juan Sun, Y. Wan
With the current rate of video data generation, there is an urgent need of automatic video content analysis for subsequent purposes such as summarization, retrieval and classification. And video shot boundary detection is usually the first step to segment a video clip into meaningful shots. Taking the processing speed into account, most state-of-the-art methods make use of the frame histogram to extract shot boundary characteristics. In this paper we propose a different approach with a novel metric, which essentially captures the observation that within any shot, a pixel value in any frame usually has a pixel value very close to it within a small neighborhood in an adjacent frame. It turns out that the proposed approach can make better use of frame structural content than the histogram approach. In addition, the proposed metric has a low computational complexity. We propose a video shot boundary detection algorithm based on the proposed metric for detecting both cut transition (CT) boundary and gradual transition (GT) boundary. Experimental results show that the proposed approach enjoys better detection rates over the state-of-the-art with competitive processing speed.
{"title":"A novel metric for efficient video shot boundary detection","authors":"Juan Sun, Y. Wan","doi":"10.1109/VCIP.2014.7051500","DOIUrl":"https://doi.org/10.1109/VCIP.2014.7051500","url":null,"abstract":"With the current rate of video data generation, there is an urgent need of automatic video content analysis for subsequent purposes such as summarization, retrieval and classification. And video shot boundary detection is usually the first step to segment a video clip into meaningful shots. Taking the processing speed into account, most state-of-the-art methods make use of the frame histogram to extract shot boundary characteristics. In this paper we propose a different approach with a novel metric, which essentially captures the observation that within any shot, a pixel value in any frame usually has a pixel value very close to it within a small neighborhood in an adjacent frame. It turns out that the proposed approach can make better use of frame structural content than the histogram approach. In addition, the proposed metric has a low computational complexity. We propose a video shot boundary detection algorithm based on the proposed metric for detecting both cut transition (CT) boundary and gradual transition (GT) boundary. Experimental results show that the proposed approach enjoys better detection rates over the state-of-the-art with competitive processing speed.","PeriodicalId":166978,"journal":{"name":"2014 IEEE Visual Communications and Image Processing Conference","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124622840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/VCIP.2014.7051585
Nicholas Attard, C. J. Debono
This paper presents the development of a fast Free-Viewpoint Video (FW) rendering algorithm that exploits the parallelism offered by General Purpose Graphics Processing Units (GPGPUs). The system generates virtual views through the use of Depth Image-Based Rendering (DIBR) algorithms, implemented using NVidia® Compute Unified Device Architecture (CUDA). A novel reference image brightness adjustment algorithm that exploits the correspondences between matching pixels in the reference images to avoid drastic brightness switching while navigating in between views is also discussed. The developed solution ensures that data transfers are kept at a minimum, thus improving the overall rendering speed. Objective and subjective test results show that, for typical free-view scenarios, the proposed algorithm can be successfully deployed in real-time FW systems, providing a good Quality of Experience (QoE).
{"title":"Implementation of fast free-viewpoint video rendering on graphics processing units","authors":"Nicholas Attard, C. J. Debono","doi":"10.1109/VCIP.2014.7051585","DOIUrl":"https://doi.org/10.1109/VCIP.2014.7051585","url":null,"abstract":"This paper presents the development of a fast Free-Viewpoint Video (FW) rendering algorithm that exploits the parallelism offered by General Purpose Graphics Processing Units (GPGPUs). The system generates virtual views through the use of Depth Image-Based Rendering (DIBR) algorithms, implemented using NVidia® Compute Unified Device Architecture (CUDA). A novel reference image brightness adjustment algorithm that exploits the correspondences between matching pixels in the reference images to avoid drastic brightness switching while navigating in between views is also discussed. The developed solution ensures that data transfers are kept at a minimum, thus improving the overall rendering speed. Objective and subjective test results show that, for typical free-view scenarios, the proposed algorithm can be successfully deployed in real-time FW systems, providing a good Quality of Experience (QoE).","PeriodicalId":166978,"journal":{"name":"2014 IEEE Visual Communications and Image Processing Conference","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124695541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/VCIP.2014.7051536
Bin Li, Jizheng Xu, Feng Wu
This paper introduces 1-D dictionary mode designed for screen content coding. Two 1-D dictionary modes are designed to improve the coding efficiency for screen content. The first one is called normal dictionary mode, in which a virtual dictionary should be maintained and all the prediction comes from the virtual dictionary. The other one is called reconstruction based dictionary mode, where no virtual dictionary is to be maintained and all the previously reconstructed pixels in the same picture can be used for prediction. Hash based search is designed to find matching for both dictionary modes efficiently. 1-D dictionary mode with variable block sizes are also supported in the proposed scheme. The experimental results show the proposed algorithm achieves about 10% ~ 18.4% bit saving for different coding structures. The bit saving is up to 60% for the proposed method.
{"title":"1-D dictionary mode for screen content coding","authors":"Bin Li, Jizheng Xu, Feng Wu","doi":"10.1109/VCIP.2014.7051536","DOIUrl":"https://doi.org/10.1109/VCIP.2014.7051536","url":null,"abstract":"This paper introduces 1-D dictionary mode designed for screen content coding. Two 1-D dictionary modes are designed to improve the coding efficiency for screen content. The first one is called normal dictionary mode, in which a virtual dictionary should be maintained and all the prediction comes from the virtual dictionary. The other one is called reconstruction based dictionary mode, where no virtual dictionary is to be maintained and all the previously reconstructed pixels in the same picture can be used for prediction. Hash based search is designed to find matching for both dictionary modes efficiently. 1-D dictionary mode with variable block sizes are also supported in the proposed scheme. The experimental results show the proposed algorithm achieves about 10% ~ 18.4% bit saving for different coding structures. The bit saving is up to 60% for the proposed method.","PeriodicalId":166978,"journal":{"name":"2014 IEEE Visual Communications and Image Processing Conference","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124754849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/VCIP.2014.7051494
Wei Zhang, A. Borji, Fuzheng Yang, Ping Jiang, Hantao Liu
Advances in image quality assessment have shown the potential added value of including visual attention aspects in objective quality metrics. Numerous models of visual saliency are implemented and integrated in different quality metrics; however, their ability of improving a metric's performance in predicting perceived image quality is not fully investigated. In this paper, we conduct an exhaustive comparison of 20 state-of-the-art saliency models in the context of image quality assessment. Experimental results show that adding computational saliency is beneficial to quality prediction in general terms. However, the amount of performance gain that can be obtained by adding saliency in quality metrics highly depends on the saliency model and on the metric.
{"title":"Studying the added value of computational saliency in objective image quality assessment","authors":"Wei Zhang, A. Borji, Fuzheng Yang, Ping Jiang, Hantao Liu","doi":"10.1109/VCIP.2014.7051494","DOIUrl":"https://doi.org/10.1109/VCIP.2014.7051494","url":null,"abstract":"Advances in image quality assessment have shown the potential added value of including visual attention aspects in objective quality metrics. Numerous models of visual saliency are implemented and integrated in different quality metrics; however, their ability of improving a metric's performance in predicting perceived image quality is not fully investigated. In this paper, we conduct an exhaustive comparison of 20 state-of-the-art saliency models in the context of image quality assessment. Experimental results show that adding computational saliency is beneficial to quality prediction in general terms. However, the amount of performance gain that can be obtained by adding saliency in quality metrics highly depends on the saliency model and on the metric.","PeriodicalId":166978,"journal":{"name":"2014 IEEE Visual Communications and Image Processing Conference","volume":"259 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123967130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/VCIP.2014.7051626
Jarno Vanne, Marko Viitanen, Ari Koivula, T. Hämäläinen
This paper compares the rate-distortion-complexity (RDC) characteristics of the HEVC Main 10 Profile (M10P) and Main Profile (MP) encoders. The evaluations are performed with HEVC reference encoder (HM) whose M10P and MP are benchmarked with different resolutions, frame rates, and bit depths. The reported RD results are based on bit rate differences for equal PSNR whereas complexities have been profiled with Intel VTune on Intel Core 2 processor. With our 10-bit 4K 120 fps test set, the average bit rate decrements of M10P over MP are 5.8%, 11.6%, and 12.3% in the all-intra (AI), random access (RA), and low-delay B (LB) configurations, respectively. Decreasing the bit depth of this test set to 8 lowers the RD gain of Ml OP only slightly to 5.4% (AI), 11.4% (RA), and 12.1% (LB). The similar trend continues in all our tests even though the RD gain of M10P is decreased over MP with lower resolutions and frame rates. M10P introduces no computational overhead in HM, but it is anticipated to increase complexity and double the memory usage in practical encoders. Hence, the 10-bit HEVC encoding with 8-bit input video is the most recommended option if computation and memory resources are adequate for it.
{"title":"Comparative study of 8 and 10-bit HEVC encoders","authors":"Jarno Vanne, Marko Viitanen, Ari Koivula, T. Hämäläinen","doi":"10.1109/VCIP.2014.7051626","DOIUrl":"https://doi.org/10.1109/VCIP.2014.7051626","url":null,"abstract":"This paper compares the rate-distortion-complexity (RDC) characteristics of the HEVC Main 10 Profile (M10P) and Main Profile (MP) encoders. The evaluations are performed with HEVC reference encoder (HM) whose M10P and MP are benchmarked with different resolutions, frame rates, and bit depths. The reported RD results are based on bit rate differences for equal PSNR whereas complexities have been profiled with Intel VTune on Intel Core 2 processor. With our 10-bit 4K 120 fps test set, the average bit rate decrements of M10P over MP are 5.8%, 11.6%, and 12.3% in the all-intra (AI), random access (RA), and low-delay B (LB) configurations, respectively. Decreasing the bit depth of this test set to 8 lowers the RD gain of Ml OP only slightly to 5.4% (AI), 11.4% (RA), and 12.1% (LB). The similar trend continues in all our tests even though the RD gain of M10P is decreased over MP with lower resolutions and frame rates. M10P introduces no computational overhead in HM, but it is anticipated to increase complexity and double the memory usage in practical encoders. Hence, the 10-bit HEVC encoding with 8-bit input video is the most recommended option if computation and memory resources are adequate for it.","PeriodicalId":166978,"journal":{"name":"2014 IEEE Visual Communications and Image Processing Conference","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114712758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/VCIP.2014.7051514
Mading Li, Jiaying Liu, J. Ren, Zongming Guo
Transform coding based on the discrete cosine transform (DCT) has been widely used in image coding standards. However, the coded images often suffer from severe visual distortions such as blocking artifacts. In this paper, we propose a novel image deblocking method to address the blocking artifacts reduction problem in a patch-based scheme. Image patches are clustered and reconstructed by the low-rank approximation, which is weighted by the geodesic distance. Experimental results show that the proposed method achieves higher PSNR than the state-of-the-art deblocking and denoising methods and the processed images present good visual quality.
{"title":"Patch-based image deblocking using geodesic distance weighted low-rank approximation","authors":"Mading Li, Jiaying Liu, J. Ren, Zongming Guo","doi":"10.1109/VCIP.2014.7051514","DOIUrl":"https://doi.org/10.1109/VCIP.2014.7051514","url":null,"abstract":"Transform coding based on the discrete cosine transform (DCT) has been widely used in image coding standards. However, the coded images often suffer from severe visual distortions such as blocking artifacts. In this paper, we propose a novel image deblocking method to address the blocking artifacts reduction problem in a patch-based scheme. Image patches are clustered and reconstructed by the low-rank approximation, which is weighted by the geodesic distance. Experimental results show that the proposed method achieves higher PSNR than the state-of-the-art deblocking and denoising methods and the processed images present good visual quality.","PeriodicalId":166978,"journal":{"name":"2014 IEEE Visual Communications and Image Processing Conference","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114823166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/VCIP.2014.7051620
Li Yu, Jimin Xiao, T. Tillo
Reed-Solomon erasure code is one of the most studied protection methods for video streaming over unreliable networks. As a block-based error correcting code, large block size and increased number of parity packets will enhance its protection performance. However, for video applications this enhancement is sacrificed by the error propagation and the increased bitrate. So, to tackle this paradox, we propose a rate-distortion optimized redundancy allocation scheme, which takes into consideration the distortion caused by losing each slice and the propagated error. Different from other approaches, the amount of introduced redundancy and the way it is introduced are automatically selected without human interventions based on the network condition and video characteristics. The redundancy allocation problem is formulated as a constraint optimization problem, which allows to have more flexibility in setting the block-wise redundancy. The proposed scheme is implemented in JM14.0 for H.264, and it achieves an average gain of 1dB over the state-of-the-art approach.
{"title":"Dynamic redundancy allocation for video streaming using Sub-GOP based FEC code","authors":"Li Yu, Jimin Xiao, T. Tillo","doi":"10.1109/VCIP.2014.7051620","DOIUrl":"https://doi.org/10.1109/VCIP.2014.7051620","url":null,"abstract":"Reed-Solomon erasure code is one of the most studied protection methods for video streaming over unreliable networks. As a block-based error correcting code, large block size and increased number of parity packets will enhance its protection performance. However, for video applications this enhancement is sacrificed by the error propagation and the increased bitrate. So, to tackle this paradox, we propose a rate-distortion optimized redundancy allocation scheme, which takes into consideration the distortion caused by losing each slice and the propagated error. Different from other approaches, the amount of introduced redundancy and the way it is introduced are automatically selected without human interventions based on the network condition and video characteristics. The redundancy allocation problem is formulated as a constraint optimization problem, which allows to have more flexibility in setting the block-wise redundancy. The proposed scheme is implemented in JM14.0 for H.264, and it achieves an average gain of 1dB over the state-of-the-art approach.","PeriodicalId":166978,"journal":{"name":"2014 IEEE Visual Communications and Image Processing Conference","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124347074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/VCIP.2014.7051601
Qiqiang Chen, Y. Wan
Impulse noise is commonly encountered during image transmission and many methods have been proposed to remove it. Although it is now possible to recover the true image reasonably well, even under severe noise (90% pixel contamination), essentially all methods published so far follow the standard procedure of noisy pixel detection/classification and then noisy pixel value reconstruction, without any further processing. In this paper we show an interesting empirical discovery that the traditionally denoised image tends to have the estimation error with a Laplacian distribution, which makes it possible to add a postprocessing stage to denoise the traditionally obtained result with this new type of noise. We propose a practical algorithm within this new framework and experimental results show that superior results can be obtained over previously published methods.
{"title":"A new framework for image impulse noise removal with postprocessing","authors":"Qiqiang Chen, Y. Wan","doi":"10.1109/VCIP.2014.7051601","DOIUrl":"https://doi.org/10.1109/VCIP.2014.7051601","url":null,"abstract":"Impulse noise is commonly encountered during image transmission and many methods have been proposed to remove it. Although it is now possible to recover the true image reasonably well, even under severe noise (90% pixel contamination), essentially all methods published so far follow the standard procedure of noisy pixel detection/classification and then noisy pixel value reconstruction, without any further processing. In this paper we show an interesting empirical discovery that the traditionally denoised image tends to have the estimation error with a Laplacian distribution, which makes it possible to add a postprocessing stage to denoise the traditionally obtained result with this new type of noise. We propose a practical algorithm within this new framework and experimental results show that superior results can be obtained over previously published methods.","PeriodicalId":166978,"journal":{"name":"2014 IEEE Visual Communications and Image Processing Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124385764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/VCIP.2014.7051596
Yung-Lin Huang, Tang-Wei Hsu, Shao-Yi Chien
Nowadays, 3D scene reconstruction using RGB-D videos becomes more popular because of the widely-available off-the-shelf RGB-D camera. However, the depth information from current RGB-D camera still need improved in order to reconstruct the 3D scene with better quality. In this paper, an edge-aware depth completion method aims to recover more accurate depth information is proposed. There are mainly two parts in our proposed method. The first part is the edge-aware color image analysis, and the second part is depth image processing including unreliable depth pixel invalidation and filling. The depth image processing can retrieve more accurate depth information using our proposed edge-aware color image analysis. Consequently, we can not only preserve the reliable depth information, but also fill in the appropriate depth values to align edges of depth image with edges of its corresponding color image. Besides, the experimental results show that the visualization of the reconstructed point-cloud 3D scene benefits from our proposed edge-aware depth completion. Finally, the PSNR evaluation using ground truth depth information is presented.
{"title":"Edge-aware depth completion for point-cloud 3D scene visualization on an RGB-D camera","authors":"Yung-Lin Huang, Tang-Wei Hsu, Shao-Yi Chien","doi":"10.1109/VCIP.2014.7051596","DOIUrl":"https://doi.org/10.1109/VCIP.2014.7051596","url":null,"abstract":"Nowadays, 3D scene reconstruction using RGB-D videos becomes more popular because of the widely-available off-the-shelf RGB-D camera. However, the depth information from current RGB-D camera still need improved in order to reconstruct the 3D scene with better quality. In this paper, an edge-aware depth completion method aims to recover more accurate depth information is proposed. There are mainly two parts in our proposed method. The first part is the edge-aware color image analysis, and the second part is depth image processing including unreliable depth pixel invalidation and filling. The depth image processing can retrieve more accurate depth information using our proposed edge-aware color image analysis. Consequently, we can not only preserve the reliable depth information, but also fill in the appropriate depth values to align edges of depth image with edges of its corresponding color image. Besides, the experimental results show that the visualization of the reconstructed point-cloud 3D scene benefits from our proposed edge-aware depth completion. Finally, the PSNR evaluation using ground truth depth information is presented.","PeriodicalId":166978,"journal":{"name":"2014 IEEE Visual Communications and Image Processing Conference","volume":"452 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125786918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/VCIP.2014.7051529
Huiying Liu, Yanwu Xu, D. Wong, Jiang Liu
Age-related Macular Degeneration (AMD) is the third leading cause of blindness. Its prevalence is increasing in these years for the coming of "aging time". Early detection and grading can prohibit it from becoming severe and protect vision. The appearance of drusen is an important indicator for AMD thus automatic drusen detection and segmentation have attracted much research attention in the past years. In this paper, we propose a novel drusen segmentation method by using Growcut. This method first detects the local maximum and minimum points. The maximum points, which are potential drusen, are then classified as drusen or non-drusen. The drusen points will be used as foreground labels while the non-drusen points together with the minima will be used as background labels. These labels are fed into Growcut to obtain the drusen boundaries. The method is tested on a manually labeled dataset with 96 images containing drusen. The experimental results verify the effectiveness of the method.
{"title":"Growcut-based drusen segmentation for age-related macular degeneration detection","authors":"Huiying Liu, Yanwu Xu, D. Wong, Jiang Liu","doi":"10.1109/VCIP.2014.7051529","DOIUrl":"https://doi.org/10.1109/VCIP.2014.7051529","url":null,"abstract":"Age-related Macular Degeneration (AMD) is the third leading cause of blindness. Its prevalence is increasing in these years for the coming of \"aging time\". Early detection and grading can prohibit it from becoming severe and protect vision. The appearance of drusen is an important indicator for AMD thus automatic drusen detection and segmentation have attracted much research attention in the past years. In this paper, we propose a novel drusen segmentation method by using Growcut. This method first detects the local maximum and minimum points. The maximum points, which are potential drusen, are then classified as drusen or non-drusen. The drusen points will be used as foreground labels while the non-drusen points together with the minima will be used as background labels. These labels are fed into Growcut to obtain the drusen boundaries. The method is tested on a manually labeled dataset with 96 images containing drusen. The experimental results verify the effectiveness of the method.","PeriodicalId":166978,"journal":{"name":"2014 IEEE Visual Communications and Image Processing Conference","volume":"152 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122050647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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