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

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Facial expression recognition based on combination of spatio-temporal and spectral features in local facial regions 基于局部区域时空特征与光谱特征相结合的面部表情识别
Pub Date : 2013-09-01 DOI: 10.1109/IRANIANMVIP.2013.6780027
Nakisa Abounasr, H. Pourghassem
This paper presents two new approaches for facial expression recognition based on digital curvelet transform and local binary patterns from three orthogonal planes (LBP-TOP) for both still image and image sequences. The features are extracted by using the digital curvelet transform on facial regions in still image. In this approach, some sub-bands correspond to angle of facial region is used. These sub-bands consist of more frequency information. The digital curvelet coefficients and LBP-TOP are represented to combine spatio-temporal and spectral features for image sequences. The obtained results by our proposed approaches on the Cohn-Kanade facial expression database have acceptable recognition rates of 91.90% and 88.38% for still image and image sequences, respectively.
针对静止图像和图像序列,提出了基于数字曲线变换和三正交平面局部二值模式(LBP-TOP)的面部表情识别新方法。利用数字曲线变换对静止图像中的人脸区域进行特征提取。在这种方法中,使用了一些与面部区域角度相对应的子带。这些子带包含更多的频率信息。利用数字曲线系数和LBP-TOP来结合图像序列的时空和光谱特征。在Cohn-Kanade面部表情数据库上,我们提出的方法对静止图像和图像序列的可接受识别率分别为91.90%和88.38%。
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引用次数: 0
A novel histogram thresholding method for surface defect detection 一种新的表面缺陷直方图阈值检测方法
Pub Date : 2013-09-01 DOI: 10.1109/IRANIANMVIP.2013.6779957
M. H. Karimi, D. Asemani
One of the most important applications of machine vision in various industries is automated inspection. Performance of automated inspection depends directly on the algorithm used for threshold selection. Common methods of automatic thresholding are based on image histogram. In previous methods, the threshold selection has been realized by dividing the histogram into two classes. Also, possibility of misdiagnosis is high especially for the textures without defect. This paper proposes a new statistical algorithm for automatic theresholding which can be optimally applied in the presence of different types of surface defects. The optimum threshold is obtained in the proposed algorithm so that a maximum between-class and minimum within-class variances are provided. Proposed methods demonstrate a better performance compared to classic histogram-based algorithm particularly for the textures without any considerable defects.
机器视觉在各个行业中最重要的应用之一是自动检测。自动检测的性能直接取决于阈值选择的算法。常用的自动阈值分割方法是基于图像直方图的。在以前的方法中,阈值选择是通过将直方图分成两类来实现的。此外,对于没有缺陷的纹理,误诊的可能性也很高。本文提出了一种新的自动阈值统计算法,该算法可以最优地应用于不同类型的表面缺陷。该算法获得了最优阈值,从而提供了最大的类间方差和最小的类内方差。与传统的基于直方图的算法相比,所提出的方法具有更好的性能,特别是在纹理上没有明显的缺陷。
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引用次数: 4
Predictive Three Step Search (PTSS) algorithm for motion estimation 预测三步搜索(PTSS)算法的运动估计
Pub Date : 2013-09-01 DOI: 10.1109/IRANIANMVIP.2013.6779948
Hadi Amirpour, A. Mousavinia, Nakisa Shamsi
Motion estimation is a vital task in video compression and many algorithms are proposed to reduce its computational complexity. In a conventional Full Search (FS) algorithm, all blocks are searched for a match in the search window, resulting in a very acceptable PSNR compared to the other methods. However it suffers from heavy computational overhead. Three Step Search (TSS) algorithm which limits the search space adaptively, is used in many applications for its simplicity and effectiveness. The PTSS algorithm proposed in this paper decreases the number of search blocks even more, using motion information obtained from its neighboring blocks. Experimental and simulation results show approximately a 20% speed enhancement with the same or slightly improved PSNR in comparison to TSS.
运动估计是视频压缩中的一项重要任务,为了降低运动估计的计算复杂度,提出了许多算法。在传统的全搜索(FS)算法中,在搜索窗口中搜索所有块以寻找匹配项,与其他方法相比,产生非常可接受的PSNR。然而,它的计算开销很大。三步搜索(Three - Step Search, TSS)算法具有自适应限制搜索空间的优点,被广泛应用。本文提出的PTSS算法利用从相邻块中获得的运动信息,进一步减少了搜索块的数量。实验和仿真结果表明,与TSS相比,在相同或略有改善的PSNR下,速度提高了约20%。
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引用次数: 10
A fast seam carving method based on merging seams in subimages 一种基于子图像接缝合并的快速缝刻方法
Pub Date : 2013-09-01 DOI: 10.1109/IRANIANMVIP.2013.6780029
F. Yaghmaee, A. A. Gharahbagh
Display devices based on its different screens and resolutions, need image resizing to retain the image's quality. Common image resizing methods cannot save or protect important objects or its results are non-photorealistic. Seam carving as a new method has been widely used for content-aware image and video resizing with little distortion in comparison with common methods. Unfortunately, seam carving is a complex algorithm and for high resolution videos or images has a long run time and is not usable in real-time applications. In this paper, a novel fast method in order to accelerate simple seam carving and decrease computational burden is presented. In this method image is divided into three equal horizontal or vertical sections, while the traditional seam carving is applied to the middle section. In the top and down sections, the algorithm estimates seam with respect to the middle part seam using an approximated Dijkstra method. Experiments have demonstrated better computational efficiency of presented method when it faces the current seam carving method. It is also preserving the image's information as effectively as the original seam carving method.
显示设备根据其不同的屏幕和分辨率,需要调整图像大小以保持图像的质量。常用的图像调整方法不能保存或保护重要对象,或者其结果不真实。接缝雕刻作为一种新的方法,在内容感知图像和视频的调整中得到了广泛的应用,与常用的方法相比,它具有较小的失真。不幸的是,接缝雕刻是一个复杂的算法,对于高分辨率的视频或图像有很长的运行时间,不能用于实时应用。本文提出了一种新的快速切缝方法,以加快简单的切缝速度,减少计算量。在这种方法中,图像被分成三个相等的水平或垂直部分,而传统的接缝雕刻应用于中间部分。在上、下两段,采用近似的Dijkstra法对中部煤层进行估计。实验结果表明,该方法在面对现有的切缝方法时具有较好的计算效率。该方法与原有的缝刻方法一样有效地保留了图像的信息。
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引用次数: 0
Ant colony alpha matte: A new approach for natural image matting 蚁群alpha抠图:一种自然图像抠图的新方法
Pub Date : 2013-09-01 DOI: 10.1109/IRANIANMVIP.2013.6779972
V. Soleimani, F. H. Vincheh
In this paper, we present an interactive algorithm to separate foreground and background regions of natural images (natural image matting) using ant colony optimization. Today, image matting is one of the most challenging and interesting research fields in image processing. In our approach instead of preparing a trimap, the user specifies foreground and background regions by some red and blue scribbles. Then by minimizing local energy function of all pixels alpha matte is estimated. Our approach not only needs a little interaction with the user but also by applying ant colony algorithm on color images, finds homogenous regions of the image and yields good results compared with other methods. In other words, the local energy of a pixel is obtained using traveled path by the pixel ant and since the ant tends to move to pixels similar to beginning pixel, homogenous regions of the image are detected. Moreover, we use some techniques like vectorization in the implementation of our algorithm in order to decrease time complexity. Experimental results show our algorithm advantages.
本文提出了一种基于蚁群优化的自然图像前景和背景区域分离的交互式算法(自然图像抠图)。图像抠图是当今图像处理中最具挑战性和最有趣的研究领域之一。在我们的方法中,用户通过一些红色和蓝色的涂鸦来指定前景和背景区域,而不是准备一个trimap。然后通过最小化所有像素的局部能量函数来估计alpha哑光。我们的方法不仅需要与用户进行少量的交互,而且通过对彩色图像应用蚁群算法,找到图像的均匀区域,与其他方法相比,取得了良好的效果。换句话说,像素蚂蚁使用行进路径获得像素的局部能量,并且由于蚂蚁倾向于移动到与起始像素相似的像素,因此检测到图像的均匀区域。此外,我们在算法的实现中使用了一些技术,如向量化,以降低时间复杂度。实验结果表明了算法的优越性。
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引用次数: 0
Accelerating of color moments and texture features extraction using GPU based parallel computing 基于GPU的并行计算加速颜色矩和纹理特征提取
Pub Date : 2013-09-01 DOI: 10.1109/IRANIANMVIP.2013.6780024
H. Heidari, A. Chalechale, A. Mohammadabadi
Image retrieval tools can assist people in making efficient use of digital image collections; also it has become imperative to find efficient methods for the retrieval of these images. Most image processing algorithms are inherently parallel, so multithreading processors are suitable in such applications. In very big image databases, image processing takes very long time for run on a single core processor because of single thread execution of algorithms. GPU is more common in most image processing applications due to multithread execution of algorithms, programmability and low cost. In this paper we implement color moments and texture based image retrieval (entropy, standard deviation and local range) in parallel using CUDA programming model to run on GPUs. These features are applied to search images from a database which are similar to a query image. We evaluated our retrieval system using recall, precision, and average precision measures. Experimental results showed that parallel implementation led to an average speed up of 144.67×over the serial implementation when running on a NVIDIA GPU GeForce GT610M. Also the average precision and the average recall of proposed method are 61.968% and 55% respectively.
图像检索工具可以帮助人们有效地利用数字图像集合;寻找有效的图像检索方法已成为当务之急。大多数图像处理算法本质上是并行的,因此多线程处理器适合于这种应用。在非常大的图像数据库中,由于算法的单线程执行,图像处理需要在单核处理器上运行很长时间。由于算法的多线程执行、可编程性和低成本,GPU在大多数图像处理应用中更为常见。本文利用CUDA编程模型在gpu上并行实现了基于颜色矩和纹理的图像检索(熵、标准差和局部范围)。这些特征应用于从数据库中搜索与查询图像相似的图像。我们使用召回率、精度和平均精度来评估我们的检索系统。实验结果表明,在NVIDIA GPU GeForce GT610M上运行时,并行实现比串行实现的平均速度提高144.67×over。平均查准率为61.968%,平均查全率为55%。
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引用次数: 12
Attention control using fuzzy inference system in monitoring CCTV based on crowd density estimation 基于人群密度估计的模糊推理系统在监控CCTV中的注意力控制
Pub Date : 2013-09-01 DOI: 10.1109/IRANIANMVIP.2013.6779979
F. Tehranipour, R. Shishegar, Soheil Tehranipour, S. Setarehdan
One important issue in machine vision is using automatic attention control methods for monitoring CCTV cameras, in order to enhance the security of people in public. Result of automatic methods such as crowd density estimation can alert the operator in the case of risk probability increasing. In addition to overall crowd density, other parameters such as regional crowd density and the temporal and spatial criteria of each frame of video should be considered to control the operator's attention correctly. For this purpose, according to the gradual change of crowd density and risk probability in daily hours and uncertainty in our knowledge in evaluation of crowded places, we designed a fuzzy decision making system to make decisions about risk probability. The design of this system is based on the fact that the human visual system tends to direct attention to events that happen with low probability. The efficiency of this system is tested on real data and results are presented to demonstrate the practical applications of this system to aid the human operator.
机器视觉中的一个重要问题是使用自动注意力控制方法来监控闭路电视摄像机,以增强公共场所人们的安全。人群密度估计等自动方法的结果可以在风险概率增加的情况下提醒操作人员。为了正确控制操作者的注意力,除了整体人群密度外,还需要考虑区域人群密度、视频每帧的时空标准等参数。为此,根据人群密度和风险概率在每天小时内的逐渐变化,以及我们对拥挤场所评价知识的不确定性,设计了一个模糊决策系统,对风险概率进行决策。这个系统的设计是基于这样一个事实,即人类的视觉系统倾向于将注意力集中在低概率发生的事件上。通过实际数据验证了该系统的有效性,并给出了该系统辅助人工操作的实际应用结果。
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引用次数: 4
A new SVD-based image quality assessment 一种新的基于奇异值分解的图像质量评价方法
Pub Date : 2013-09-01 DOI: 10.1109/IRANIANMVIP.2013.6780013
Mohammad Esmaeilpour, Azadeh Mansouri, Ahmad Mahmoudi-Aznaveh
In recent years, many efforts have been performed in order to design an algorithm assessing perceptual image quality based on human visual system. Although some impressive metrics have been presented, full reference image quality assessment (IQA) is still a challenging issue. In this paper, we present a new SVD-based IQA method in which the structural similarity between the reference and distorted image is utilized as a key factor for measuring the imposed distortions. The experimental results show that the proposed algorithm can effectively evaluated the image quality in a consistent manner with human visual perception.
近年来,为了设计一种基于人类视觉系统的感知图像质量评估算法,人们做了很多努力。尽管已经提出了一些令人印象深刻的指标,但完全参考图像质量评估(IQA)仍然是一个具有挑战性的问题。在本文中,我们提出了一种新的基于奇异值分解的IQA方法,该方法利用参考图像和失真图像之间的结构相似性作为测量施加畸变的关键因素。实验结果表明,该算法能够有效地评估图像质量,且与人类视觉感知一致。
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引用次数: 5
Content based video retrieval using information theory 基于信息理论的视频内容检索
Pub Date : 2013-09-01 DOI: 10.1109/IRANIANMVIP.2013.6779981
Hadi Yarmohammadi, M. Rahmati, Shahram Khadivi
During the last decades a large set of video archives is created and rapidly multimedia growth creates new challenge in the image processing world. A reliable system is needed to automate the process of this large amount of data. Video analyses are done in two different levels, low level and high level. There are many problems in video content analysis and in this work we analyzed content based video analysis. Our proposed method is based on Information theory. These systems consist of three main parts which includes: Shot Boundary Detection, Hierarchical video summarization, retrieve and index target video. System performance is evaluated on TRECVID2006 Database, results shown the usefulness of the proposed method.
在过去的几十年里,大量的视频档案被创建,多媒体的快速发展给图像处理领域带来了新的挑战。需要一个可靠的系统来自动化处理这些大量数据。视频分析分为低级和高级两个层次。针对视频内容分析中存在的诸多问题,本文对基于内容的视频分析进行了分析。我们提出的方法是基于信息论的。该系统主要包括三个部分:镜头边界检测、分层视频摘要、目标视频检索和索引。在TRECVID2006数据库上对系统性能进行了评估,结果表明了该方法的有效性。
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引用次数: 12
Malaria parasite detection in giemsa-stained blood cell images 吉姆萨染色血细胞图像中的疟疾寄生虫检测
Pub Date : 2013-09-01 DOI: 10.1109/IRANIANMVIP.2013.6780011
Leila Malihi, K. Ansari-Asl, A. Behbahani
This research represents a method to detect malaria parasite in blood samples stained with giemsa. In order to increase the accuracy of detecting, at the first step, the red blood cell mask is extracted. It is due to the fact that most of malaria parasites exist in red blood cells. Then, stained elements of blood such as red blood cells, parasites and white blood cells are extracted. At the next step, red blood cell mask is located on the extracted stained elements to separate the possible parasites. Finally, color histogram, granulometry, gradient and flat texture features are extracted and used as classifier inputs. Here, five classifiers were used: support vector machines (SVM), nearest mean (NM), K nearest neighbors (KNN), 1-NN and Fisher. In this research K nearest neighbors classifier had the best accuracy, which was 91%.
本研究提出了一种检测吉氏菌染色血样中疟原虫的方法。为了提高检测的准确性,在第一步提取红细胞掩膜。这是因为大多数疟疾寄生虫存在于红细胞中。然后,提取血液中的染色成分,如红细胞、寄生虫和白细胞。下一步,在提取的染色元素上放置红细胞掩膜,以分离可能的寄生虫。最后,提取颜色直方图、粒度特征、梯度特征和平面纹理特征作为分类器输入。这里使用了五种分类器:支持向量机(SVM)、最接近均值(NM)、K近邻(KNN)、1-NN和Fisher。在本研究中,K近邻分类器的准确率最高,为91%。
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引用次数: 45
期刊
2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP)
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