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2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP)最新文献

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Brain blood vessel map extraction using wavelet-based DSA fusion 基于小波的DSA融合脑血管图提取
2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP) Pub Date : 2013-09-01 DOI: 10.1109/IRANIANMVIP.2013.6780021
Saba Momeni, H. Pourghassem
{"title":"Brain blood vessel map extraction using wavelet-based DSA fusion","authors":"Saba Momeni, H. Pourghassem","doi":"10.1109/IRANIANMVIP.2013.6780021","DOIUrl":"https://doi.org/10.1109/IRANIANMVIP.2013.6780021","url":null,"abstract":"Recently image fusion has prominent and applicable roles in medical image processing. Digital subtraction angiography (DSA) image is applied to display map of blood vessels. In this paper, a new fusion algorithm for DSA serial images based on discrete wavelet transform coefficients is proposed. Our algorithm will be compared for different wavelet transforms and activity criteria for high frequency coefficients. The comparisons are based on the objective evaluation criteria which show measure of noise existence, sharpness and correlation between the fusion result and reference image. Finally, we specify which type of wavelet transform and activity criterion results more informative brain blood vessel map.","PeriodicalId":297204,"journal":{"name":"2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126745091","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}
引用次数: 1
Denoising by averaging reconstructed images: Using Singularity Function Analysis 利用奇异函数分析对重构图像进行平均去噪
2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP) Pub Date : 2013-09-01 DOI: 10.1109/IRANIANMVIP.2013.6779995
M. Shafiee, M. Karami, Kaveh Kangarloo
{"title":"Denoising by averaging reconstructed images: Using Singularity Function Analysis","authors":"M. Shafiee, M. Karami, Kaveh Kangarloo","doi":"10.1109/IRANIANMVIP.2013.6779995","DOIUrl":"https://doi.org/10.1109/IRANIANMVIP.2013.6779995","url":null,"abstract":"A newfound method of denoising that based on Averaging Reconstructed Image (AVREC), is used. The approach was proposed on signals, approximately about last decade, Since 2004. In definition (procedure), first of all, we divide the spectrum of noisy image into several images that can be then, reconstructed with 2-D Singularity Function Analysis (SFA) model. Among this mathematical model, each matrix or a discrete set of data, represents as a weighted sum of singularity functions. In image denoising field, this technique, rebuilt all lost high frequencies parameters that are essential. Illustrate each new image, as a sum of noise-free image and the small noise. So on, we can then, denoise image by averaging reconstructed ones. Both theoretical and experimental results on standard gray-scale images, confirm the advantages (benefits) of this approach as an applicable method of denoising.","PeriodicalId":297204,"journal":{"name":"2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124459377","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}
引用次数: 1
Compressed sensing and multiple image fusion: An information theoretic approach 压缩感知与多图像融合:一种信息论方法
2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP) Pub Date : 2013-09-01 DOI: 10.1109/IRANIANMVIP.2013.6780007
Kamran Keykhosravi, S. Mashhadi
{"title":"Compressed sensing and multiple image fusion: An information theoretic approach","authors":"Kamran Keykhosravi, S. Mashhadi","doi":"10.1109/IRANIANMVIP.2013.6780007","DOIUrl":"https://doi.org/10.1109/IRANIANMVIP.2013.6780007","url":null,"abstract":"In this paper, we propose an information theoretic approach to fuse images compressed by compressed sensing (CS) techniques. The goal is to fuse multiple compressed images directly using measurements and reconstruct the final image only once. Since the reconstruction is the most expensive step, it would be a more economic method than separate reconstruction of each image. The proposed scheme is based on calculating the result using weighted average on the measurements of the inputs, where weights are calculated by information theoretic functions. The simulation results show that the final images produced by our method have higher quality than those produced by traditional methods, especially if the number of input images exceeds two.","PeriodicalId":297204,"journal":{"name":"2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122720642","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}
引用次数: 0
A new framework for goal detection based on semantic events detection in soccer video 基于语义事件检测的足球视频目标检测新框架
2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP) Pub Date : 2013-09-01 DOI: 10.1109/IRANIANMVIP.2013.6779975
Farshad Bayat, M. Moin, Farhad Bayat, M. Mokhtari
{"title":"A new framework for goal detection based on semantic events detection in soccer video","authors":"Farshad Bayat, M. Moin, Farhad Bayat, M. Mokhtari","doi":"10.1109/IRANIANMVIP.2013.6779975","DOIUrl":"https://doi.org/10.1109/IRANIANMVIP.2013.6779975","url":null,"abstract":"Soccer video processing and analysis to find critical events such as occurrences of goal event have been one of the important issues and topics of active researches in recent years. In this paper, a new role-based framework is proposed for goal event detection in which the semantic structure of soccer game is used. Usually after a goal scene, the audiences' and reporters' sound intensity is increased, ball is sent back to the center and the camera may: zoom on Player, show audiences' delighting, repeat the goal scene or display a combination of them. Thus, the occurrence of goal event will be detectable by analysis of sequences of above roles. The proposed framework in this paper consists of four main procedures: 1-detection of game's critical events by using audio channel, 2-detection of shot boundary and shots classification, 3-selection of candidate events according to the type of shot and existence of goalmouth in the shot, 4-detection of restarting the game from the center of the field. A new method for shot classification is also presented in this framework. Finally, by applying the proposed method it was shown that the goal events detection has a good accuracy and the percentage of detection failure is also very low.","PeriodicalId":297204,"journal":{"name":"2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123833048","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}
引用次数: 2
Evolutionary fractal image compression using asexual reproduction optimization with guided mutation 引导突变无性生殖优化的进化分形图像压缩
2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP) Pub Date : 2013-09-01 DOI: 10.1109/IRANIANMVIP.2013.6780022
S. Mahmoudi, Ebrahim Jelvehfard, M. Moin
{"title":"Evolutionary fractal image compression using asexual reproduction optimization with guided mutation","authors":"S. Mahmoudi, Ebrahim Jelvehfard, M. Moin","doi":"10.1109/IRANIANMVIP.2013.6780022","DOIUrl":"https://doi.org/10.1109/IRANIANMVIP.2013.6780022","url":null,"abstract":"There are many different methods for image compression which each of them satisfies a various type of purposes. Fractal Image Compression is a category of these techniques that has some specific features. This method is robust against aliasing of images in zooming, so it has multi-resolution capability. Besides, compression ratio of this method is reasonably competitive, also its decoding is fast. But the main issue of this method is the compression time which is very high because of complexity for finding self-similar blocks. So researchers have tried to mitigate computational costs with different approaches. In this paper, using an evolutionary algorithm called Asexual Reproduction Optimization (ARO) is proposed for fractal image compression. Then the main operator of this algorithm is tuned to make it more efficient versus other individual-based algorithms like Simulated Annealing (SA) and Tabu Search (TS). Finally experimental results and execution time of the proposed method, SA and full search are compared. ARO with guided mutation generates defensible outputs in very short time versus the others approaches.","PeriodicalId":297204,"journal":{"name":"2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131761221","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}
引用次数: 2
Low complexity distributed video coding using compressed sensing 基于压缩感知的低复杂度分布式视频编码
2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP) Pub Date : 2013-09-01 DOI: 10.1109/IRANIANMVIP.2013.6779949
S. Roohi, M. Noorhosseini, J. Zamani, H. S. Rad
{"title":"Low complexity distributed video coding using compressed sensing","authors":"S. Roohi, M. Noorhosseini, J. Zamani, H. S. Rad","doi":"10.1109/IRANIANMVIP.2013.6779949","DOIUrl":"https://doi.org/10.1109/IRANIANMVIP.2013.6779949","url":null,"abstract":"Compressive sensing (CS) is an efficient method to reconstruct sparse images with under-sampled data. In this method sensing and coding steps integrated to a one-step, low-complexity measurement acquisition system. In this paper, we use a Non-linear Conjugate Gradient (NLCG) algorithm to significantly increase the quality of reconstructed frames of video sequences. Our proposed framework divides sequence of a video to several groups of pictures (GOPs), where each GOP consisting of one key frame followed by two non-key frames. CS is then applied on each key and non-key frame with different sampling rates. For reconstruction final frames, NLCG algorithm was performed on each key frame with acceptable fidelity. To achieve desired quality on low-rate sampled non-key frames, NLCG modified using side information (SI) obtained from last two successive reconstructed key frames. Based on some performance measures such as SNR, PSNR, SSIM and RSE, our implementation results indicate that employing NLCG with Gaussian sampling matrix outperforms other methods in quality measures.","PeriodicalId":297204,"journal":{"name":"2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121076879","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}
引用次数: 7
Whale algorithm for image processing, a hardware implementation 鲸鱼算法用于图像处理，一个硬件实现
2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP) Pub Date : 2013-09-01 DOI: 10.1109/IRANIANMVIP.2013.6780010
M. Zakerhaghighi, H. Naji
{"title":"Whale algorithm for image processing, a hardware implementation","authors":"M. Zakerhaghighi, H. Naji","doi":"10.1109/IRANIANMVIP.2013.6780010","DOIUrl":"https://doi.org/10.1109/IRANIANMVIP.2013.6780010","url":null,"abstract":"The life of a kind of whale is very interesting and it is in some cases close to human life. One of the interesting and fascinating things about whales is the way they hunt. In this article, an algorithm is presented with the inspiration of the way these whales hunt. This algorithm has a wide range of applications, In order to show the capabilities of this algorithm, one of the image processing techniques is optimized and implemented using the algorithm mentioned above. We got excellent results in the execution speed and image quality. The algorithm is implemented on Spartan 3s400 FPGA.","PeriodicalId":297204,"journal":{"name":"2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116475085","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}
引用次数: 2
Intelligent detection of the falls in the elderly using fuzzy inference system and video-based motion estimation method 基于模糊推理系统和基于视频的运动估计方法的老年人跌倒智能检测
2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP) Pub Date : 2013-09-01 DOI: 10.1109/IRANIANMVIP.2013.6779996
K. Rezaee, J. Haddadnia, A. Delbari
{"title":"Intelligent detection of the falls in the elderly using fuzzy inference system and video-based motion estimation method","authors":"K. Rezaee, J. Haddadnia, A. Delbari","doi":"10.1109/IRANIANMVIP.2013.6779996","DOIUrl":"https://doi.org/10.1109/IRANIANMVIP.2013.6779996","url":null,"abstract":"Automatic detection of the abnormal walking in people, especially such accidents as the falls in the elderly, based on image processing techniques and computer vision can help develop an efficient system that its implementation in various contexts enables us to monitor people's movements. This paper proposes a new algorithm, which drawing on fuzzy rules in classification of movements as well as the implementation of the motion estimation, allows the rapid processing of the input data. At the testing stage, 57425 video frames received from Mother Nursing Home in Farzanegan and the video sequences containing the falls of the elderly were used. The results show that the values of average accuracy (AAC), detection rate (DR) and false alarm rate (FAR) were at an acceptable level, respectively with 93%, 89% and 5%. Compared to the similar techniques, the implementation of the proposed system in nursing homes and residential areas allow the real time and intelligent monitoring of the people.","PeriodicalId":297204,"journal":{"name":"2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129484017","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}
引用次数: 9
Ruling lines removal in handwritten documents 手写文件中裁断线的移除
2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP) Pub Date : 2013-09-01 DOI: 10.1109/IRANIANMVIP.2013.6779954
F. Alipour, K. Faez, Sahar Seifzadeh
{"title":"Ruling lines removal in handwritten documents","authors":"F. Alipour, K. Faez, Sahar Seifzadeh","doi":"10.1109/IRANIANMVIP.2013.6779954","DOIUrl":"https://doi.org/10.1109/IRANIANMVIP.2013.6779954","url":null,"abstract":"In this paper, we present a method for removing ruling lines from handwritten documents, making no damage to the existing characters. It is argued that ruling lines have a predictable position in the page, but their thickness and the distance between them may differ from one document to another, which is estimated with simple algorithm. Another important challenge in this regard is detecting the edge of the line. In this paper the two columns that best represent edge of the main lines are considered. Compare to other methods, our method, which has been tested on six languages, that is English, French, German, Greek, Arabic and Persian, displays reduced time in the computation of rule-line removal and higher performance.","PeriodicalId":297204,"journal":{"name":"2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP)","volume":" 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133052588","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}
引用次数: 2
Fast saliency map extraction from video: A hardware approach 从视频中快速提取显著性地图:一种硬件方法
2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP) Pub Date : 2013-09-01 DOI: 10.1109/IRANIANMVIP.2013.6779951
Amin Moradhasel, Babak Nadjar Araabi, S. M. Fakhraie, M. N. Ahmadabadi
{"title":"Fast saliency map extraction from video: A hardware approach","authors":"Amin Moradhasel, Babak Nadjar Araabi, S. M. Fakhraie, M. N. Ahmadabadi","doi":"10.1109/IRANIANMVIP.2013.6779951","DOIUrl":"https://doi.org/10.1109/IRANIANMVIP.2013.6779951","url":null,"abstract":"Saliency map is a central part of many visual attention systems, particularly during learning and control of bottom-up attention. In this research we developed a hardware tool to extract saliency map from a video sequence. Saliency map is obtained by aggregating primary features of each frame, such as intensity, color, and lines orientation, along with temporal difference. The system is designed to provide both high speed and acceptable accuracy for real-time applications, such as machine vision and robotics. A versatile Verilog model for realization of the video processing system is developed, which can easily be mapped and synthesized on various FPGA or ASIC platforms. The proposed parallel hardware can process over 50 million pixels in a second, which is about 2x faster than the state-of-the-art designs. Experimental results on sample images justify the applicability and efficiency of the developed system in real-time applications.","PeriodicalId":297204,"journal":{"name":"2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP)","volume":"406 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132578473","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}
引用次数: 3
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