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2015 9th Iranian Conference on Machine Vision and Image Processing (MVIP)最新文献

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Recovering intrinsic images: An evolutionary technique for entropy minimization 恢复内在图像:一种熵最小化的进化技术
2015 9th Iranian Conference on Machine Vision and Image Processing (MVIP) Pub Date : 2015-11-01 DOI: 10.1109/IRANIANMVIP.2015.7397503
Payam Ahmadvand, P. Ahmadvand
{"title":"Recovering intrinsic images: An evolutionary technique for entropy minimization","authors":"Payam Ahmadvand, P. Ahmadvand","doi":"10.1109/IRANIANMVIP.2015.7397503","DOIUrl":"https://doi.org/10.1109/IRANIANMVIP.2015.7397503","url":null,"abstract":"Shadow removal from color images is considered as a challenging task during last decades. Several approaches have been introduced to address and improve this task. A major breakthrough in this area is projecting the correct direction that minimizes the entropy to get rid of the lighting effect. In this work, we reduce the computational time of entropy minimization up to 52% and decrease the number of integrations by a factor of three using genetic algorithm. The first population is generated by considering the distribution of training images. Then, crossover and mutation are applied and after few generations, the algorithm can reach to the minimum entropy. In the second contribution, another system is proposed based on genetic algorithm that pave the way for finding a real number, instead of integer number, for entropy minimization. Thanks to the new method, the result shows that a real number for the angle can be accurately found on the reasonable time.","PeriodicalId":326511,"journal":{"name":"2015 9th Iranian Conference on Machine Vision and Image Processing (MVIP)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126382755","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
Painting style classification in Persian Miniatures 波斯微缩画的绘画风格分类
2015 9th Iranian Conference on Machine Vision and Image Processing (MVIP) Pub Date : 2015-11-01 DOI: 10.1109/IRANIANMVIP.2015.7397538
Solale Tabarestani, M. Eslami, Farah Torkamni-Azar
{"title":"Painting style classification in Persian Miniatures","authors":"Solale Tabarestani, M. Eslami, Farah Torkamni-Azar","doi":"10.1109/IRANIANMVIP.2015.7397538","DOIUrl":"https://doi.org/10.1109/IRANIANMVIP.2015.7397538","url":null,"abstract":"Intelligent analysis of paintings and visual arts is an interesting cross-disciplinary research domain. Although in recent years, computational painting and analyzing visual arts is highly considered by researchers, little research has been reported on unique Persian painting styles. NegarGari which is usually called as Persian Miniature is one of the most famous Miniature painting styles in the world. In this paper, we gathered a dataset for NegarGari painting style and two types of styles: Traditional and Modern NegarGari has been introduced. We investigated painting style classification task and the performance of corresponding methods is studied on Negargari along with a comparison with other well-known western styles. According to the results, classification methods shows challenging performance on western and Iranian miniature, however traditional NegarGari can be classified more easily than modern NegarGari.","PeriodicalId":326511,"journal":{"name":"2015 9th Iranian Conference on Machine Vision and Image Processing (MVIP)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132641844","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
A modified nonlinear filtering technique for removal of high density salt and pepper noise 一种用于去除高密度椒盐噪声的改进非线性滤波技术
2015 9th Iranian Conference on Machine Vision and Image Processing (MVIP) Pub Date : 2015-11-01 DOI: 10.1109/IRANIANMVIP.2015.7397523
Aref Shams-Baboli, A. Shams-Baboli
{"title":"A modified nonlinear filtering technique for removal of high density salt and pepper noise","authors":"Aref Shams-Baboli, A. Shams-Baboli","doi":"10.1109/IRANIANMVIP.2015.7397523","DOIUrl":"https://doi.org/10.1109/IRANIANMVIP.2015.7397523","url":null,"abstract":"In this paper, a very effective nonlinear filtering technique is presented for denoising the image with severe salt & pepper noise. The filter reconstruct a corrupted pixel in three steps: first, it will be replaced by the median of the uncorrupted pixels of its neighbors or average value of them if all of them were noisy. Second, the impulse noises that made in the first step will be found and replaced by salt & pepper noise, third we replace the remaining corrupted pixel by the median or its neighbor's pixel value. The algorithm takes no action on healthy pixels. The proposed algorithm is more effective in removing the salt & pepper noise and also keeps the image features. This algorithm will be test and evaluated by Lena, Boat and Lotus. The results of the simulation show that the proposed method can eliminate salt and pepper noise of densities up to 80% while keeping the edges and fine details sufficiently. Our algorithm has a better performance on all the experiments and shows much more robustness than other algorithms.","PeriodicalId":326511,"journal":{"name":"2015 9th Iranian Conference on Machine Vision and Image Processing (MVIP)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133832703","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
TeMu-app: Music characters recognition using HOG and SVM TeMu-app:基于HOG和SVM的音乐字符识别
2015 9th Iranian Conference on Machine Vision and Image Processing (MVIP) Pub Date : 2015-11-01 DOI: 10.1109/IRANIANMVIP.2015.7397520
M. Akbari, Alireza Tavakoli Targhi, Mohammad Mahdi Dehshibi
{"title":"TeMu-app: Music characters recognition using HOG and SVM","authors":"M. Akbari, Alireza Tavakoli Targhi, Mohammad Mahdi Dehshibi","doi":"10.1109/IRANIANMVIP.2015.7397520","DOIUrl":"https://doi.org/10.1109/IRANIANMVIP.2015.7397520","url":null,"abstract":"Conventionally, music sharing has been done through two ways: aural transmission and in the form of written documents which is normally called musical scores. As many of these paper based scores have not been published they are subjected to be damaged. To preserve the music an application that has the capability of digitalizing these symbolic images and creating new scores is required. Meanwhile, learning how to read a music score and, then, playing it on a musical instrument are difficult tasks to most beginner music learners. Therefore, an automatic system to understand the music score and to play its rhythms would ease their learning process. In this paper, a mobile application is developed to reach the mentioned aims. Proposed algorithm consists of several key steps including: (1) preprocessing in which the skewness and illumination issues are fixed, (2) segmentation in which the symbols are extracted followed by staff line detection and erosion, (3) feature extraction where the HOG discriminative features make the feature space, and, (4) recognition to which a multi-class SVM is applied. It was observed in the course of experiments that the propose method is resists against affine transformation and reach the accuracy of 94.24% in recognition process.","PeriodicalId":326511,"journal":{"name":"2015 9th Iranian Conference on Machine Vision and Image Processing (MVIP)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114301518","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: 4
Error compensation and hardware reduction of fixed point 2-D Gaussian filter 定点二维高斯滤波器的误差补偿与硬件缩减
2015 9th Iranian Conference on Machine Vision and Image Processing (MVIP) Pub Date : 2015-11-01 DOI: 10.1109/IRANIANMVIP.2015.7397510
M. Hajabdollahi, S. Samavi, N. Karimi
{"title":"Error compensation and hardware reduction of fixed point 2-D Gaussian filter","authors":"M. Hajabdollahi, S. Samavi, N. Karimi","doi":"10.1109/IRANIANMVIP.2015.7397510","DOIUrl":"https://doi.org/10.1109/IRANIANMVIP.2015.7397510","url":null,"abstract":"Gaussian filter is used as an efficient preprocessing method in wide ranges of image processing applications to reduce the effect of unwanted and destructive pixels of image. An efficient implementation of Gaussian filter on hardware is important especially in the real time applications. In this paper fixed point representation of Gaussian filter is considered and optimization techniques in its hardware implementation are generalized. In the proposed method the hardware cost and accuracy are in tradeoff with other and can be modified in a good manner. The simulation results show that in the case of un-sharp masking with Gaussian kernel, suitable result in term of hardware complexity and accuracy is obtained.","PeriodicalId":326511,"journal":{"name":"2015 9th Iranian Conference on Machine Vision and Image Processing (MVIP)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117245686","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
Smooth downsampling of depth images for visual prostheses 视觉假体深度图像的平滑下采样
2015 9th Iranian Conference on Machine Vision and Image Processing (MVIP) Pub Date : 2015-11-01 DOI: 10.1109/IRANIANMVIP.2015.7397527
Benyamin Kheradvar, A. Mousavinia, A. M. Sodagar
{"title":"Smooth downsampling of depth images for visual prostheses","authors":"Benyamin Kheradvar, A. Mousavinia, A. M. Sodagar","doi":"10.1109/IRANIANMVIP.2015.7397527","DOIUrl":"https://doi.org/10.1109/IRANIANMVIP.2015.7397527","url":null,"abstract":"Over the past few decades, a variety of visual prostheses is developed to allow for the restoration of the vision for the blind. In visual prostheses, visual perception is limited to extremely low image resolution mainly due to restrictions in the fabrication of efficient microelectrode arrays. As a result, tasks such as navigation and way finding become difficult for those using implantable visual prostheses. Depth cue is a suitable alternative to intensity images to improve the quality and success of the aforementioned tasks in patients. After the processing of depth images, intensity of an object depends on its distance from the patient. Based on this principle, a method for preprocessing and downsampling of the depth images is proposed in this paper. We propose a method to enhance the contrast of the depth images and downsample the results to 6 × 12 images. This paper analyzes common downsampling methods and proposes a method based on the mode function. In the proposed method, the mode function is applied on every four successive frames to use temporal information in addition to stationary information. Quantitative and qualitative evaluations upon the LIRIS dataset are presented to compare the results of proposed method with rivals.","PeriodicalId":326511,"journal":{"name":"2015 9th Iranian Conference on Machine Vision and Image Processing (MVIP)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126447407","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 homography refinement in soccer videos 在足球视频的快速同形修饰
2015 9th Iranian Conference on Machine Vision and Image Processing (MVIP) Pub Date : 2015-11-01 DOI: 10.1109/IRANIANMVIP.2015.7397533
M. Hadian, S. Kasaei
{"title":"Fast homography refinement in soccer videos","authors":"M. Hadian, S. Kasaei","doi":"10.1109/IRANIANMVIP.2015.7397533","DOIUrl":"https://doi.org/10.1109/IRANIANMVIP.2015.7397533","url":null,"abstract":"Sports video analysis and camera calibration are important applications which rely on accurate homography computation as a challenging task. Homography refinement is an important step in the task of accurate homography computation and homography tracking. Also, in certain applications (such as homography tracking) the process speed is of great importance. A robust and fast method for accurate refinement of highly inaccurate homographies in soccer video frames is proposed in this paper. To achieve that goal, a new homography model fitting method named the point-line (PL) method is proposed. It uses point-line correspondences to compute the homography, rather than point correspondences or line correspondences used by the common direct linear transformation (DLT) method. The method can be used as a fast homography refinement algorithm but it is sensitive to outliers. In order to make it robust to outliers, the PL method is employed in two different schemes: a random sample consensus (RANSAC) scheme and an iterative scheme. The two schemes are then evaluated on a set of video frames and are compared to the state-of-the-art methods. They are proved to be accurate and robust to noise and one of them is at least 3.9 times faster in soccer penalty area scenes.","PeriodicalId":326511,"journal":{"name":"2015 9th Iranian Conference on Machine Vision and Image Processing (MVIP)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130262355","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: 4
Early termination algorithm for CU size decision in HEVC intra coding HEVC编码中CU大小决定的早期终止算法
2015 9th Iranian Conference on Machine Vision and Image Processing (MVIP) Pub Date : 2015-11-01 DOI: 10.1109/IRANIANMVIP.2015.7397501
M. Ramezanpour, F. Zargari
{"title":"Early termination algorithm for CU size decision in HEVC intra coding","authors":"M. Ramezanpour, F. Zargari","doi":"10.1109/IRANIANMVIP.2015.7397501","DOIUrl":"https://doi.org/10.1109/IRANIANMVIP.2015.7397501","url":null,"abstract":"Intra coding in the High Efficiency Video Coding (HEVC) standard can significantly improve the compression efficiency but increasing the number of intra prediction modes and also higher number of Coding Unit (CU) sizes in the HEVC standard imposes much higher computational load compared with intra prediction in H.264/AVC, which substantially is computational intensive. To reduce the intra coding complexity in HEVC, this paper presents an early termination algorithm for intra prediction. The proposed method is based on the fact that a homogenous region can be predicted with larger CUs. As a result, when the proposed smoothness parameter is lower than a predefined threshold, only the prediction modes in the current CU are evaluated. Experimental results indicate that the proposed algorithm can provide on average 27.5% time saving with only 0.4% BD-rate loss whereas it maintains the same coding video quality compared with HEVC reference software, HM15.0, in all intra-main configuration.","PeriodicalId":326511,"journal":{"name":"2015 9th Iranian Conference on Machine Vision and Image Processing (MVIP)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121608371","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: 15
RGBD image segmentation RGBD图像分割
2015 9th Iranian Conference on Machine Vision and Image Processing (MVIP) Pub Date : 2015-11-01 DOI: 10.1109/IRANIANMVIP.2015.7397500
S. Mirkamali, P. Nagabhushan
{"title":"RGBD image segmentation","authors":"S. Mirkamali, P. Nagabhushan","doi":"10.1109/IRANIANMVIP.2015.7397500","DOIUrl":"https://doi.org/10.1109/IRANIANMVIP.2015.7397500","url":null,"abstract":"In this paper we present a method to segment RGBD image of a scene into coherent and meaningful parts using both the appearance features and depth information. The segmentation method is totally based on graph cuts theory which uses our proposed unsupervised Conditional Random Field (CRF) model. We evaluate our method both quantitatively and qualitatively on a set of RGBD images of NYU dataset. The results show that the combination of unsupervised CRF with graph cuts can be as accurate as supervised methods and in some cases can perform better than other segmentation methods.","PeriodicalId":326511,"journal":{"name":"2015 9th Iranian Conference on Machine Vision and Image Processing (MVIP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131001084","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
Automatic classification of travertine stones based on sum and difference histograms algorithm 基于和差直方图算法的钙华石自动分类
2015 9th Iranian Conference on Machine Vision and Image Processing (MVIP) Pub Date : 2015-11-01 DOI: 10.1109/IRANIANMVIP.2015.7397521
M. Abadi, Navid Banihashemi
{"title":"Automatic classification of travertine stones based on sum and difference histograms algorithm","authors":"M. Abadi, Navid Banihashemi","doi":"10.1109/IRANIANMVIP.2015.7397521","DOIUrl":"https://doi.org/10.1109/IRANIANMVIP.2015.7397521","url":null,"abstract":"Many industrial machines are used in travertine stone industry. But classification of this type of stone in terms of quality and appearance is generally done by human experts. Using of human experts for classification has a lot of errors, times, and costs. The reason of choosing of travertine stone is the large variety and increasing use of this stone in the building industry. Also, the classification problem in this stone has not been studied yet. Therefore, the need of automatic and computerized methods for classification of travertine stone is very useful. In this study, a set of travertine stones including 124 images from four groups was prepared. The feature extraction approach called sum and difference histogram (SDH) is used and several classification algorithms are applied. The simulation results show that the proposed approach has acceptable classification performance in travertine stones.","PeriodicalId":326511,"journal":{"name":"2015 9th Iranian Conference on Machine Vision and Image Processing (MVIP)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128615208","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
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