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2014 Fifth International Conference on Signal and Image Processing最新文献

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Discriminative DCT: An Efficient and Accurate Approach for Off-Line Signature Verification 判别式DCT:一种高效、准确的离线签名验证方法
Pub Date : 2014-01-08 DOI: 10.1109/ICSIP.2014.34
R. Bharathi, B. H. Shekar
In this paper, we proposed to combine the transform based approach with dimensionality reduction technique for off-line signature verification. The proposed approach has four major phases: Preprocessing, Feature extraction, Feature reduction and Classification. In the feature extraction phase, Discrete Cosine Transform (DCT) is employed on the signature image to obtain the upper-left corner block of size mX n as a representative feature vector. These features are subjected to Linear Discriminant Analysis (LDA) for further reduction and representing the signature with optimal set of features. Thus obtained features from all the samples in the dataset form the knowledge base. The Support Vector Machine (SVM), a bilinear classifier is used for classification and the performance is measured through FAR/FRR metric. Experiments have been conducted on standard signature datasets namely CEDAR and GPDS-160, and MUKOS, a regional language (Kannada) dataset. The comparative study is also provided with the well known approaches to exhibit the performance of the proposed approach.
本文提出了将基于变换的方法与降维技术相结合的离线签名验证方法。该方法分为预处理、特征提取、特征约简和分类四个主要阶段。在特征提取阶段,对签名图像进行离散余弦变换(DCT),得到大小为mX n的左上角块作为代表性特征向量。这些特征经过线性判别分析(LDA)进一步约简,用最优特征集表示签名。从而从数据集中的所有样本中获得特征,形成知识库。使用双线性分类器支持向量机(SVM)进行分类,并通过FAR/FRR度量度量性能。在CEDAR和GPDS-160标准签名数据集以及Kannada区域语言数据集MUKOS上进行了实验。通过比较研究,还提供了一些已知的方法来展示所提出方法的性能。
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引用次数: 4
Patch Based Image Completion for Compression Application 基于补丁的图像补全压缩应用
Pub Date : 2014-01-08 DOI: 10.1109/ICSIP.2014.20
V. Yatnalli, K. Sudha
A new technique for the filling-in of missing blocks in wireless transmission of block based compressed images is proposed. By intentionally (and automatically) dropping image blocks and using filling-in approach, the performance of the compression ratio can be improved. The approach removes only partial regions in the image and generates a smaller image of same size as the original. This provides the condensed description of an image. Intuitively, the approach at decoder side restores large dropped regions utilizing the correlations between image patches. Thus, patch manipulation technique enhances the compression ratio of still images by recovering the damaged portions of an image.
提出了一种基于块的压缩图像无线传输中缺失块的填充新技术。通过有意(和自动)删除图像块并使用填充方法,可以提高压缩比的性能。该方法仅去除图像中的部分区域,并生成与原始图像大小相同的较小图像。这提供了图像的浓缩描述。直观地,解码器侧的方法利用图像补丁之间的相关性恢复大的下降区域。因此,补丁操作技术通过恢复图像的损坏部分来提高静态图像的压缩比。
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引用次数: 4
Automatic Detection and Elimination of an Optic Disc for Improving Drusen Detection Accuracy 视盘的自动检测与消除,提高Drusen检测精度
Pub Date : 2014-01-08 DOI: 10.1109/ICSIP.2014.23
A. Prasath, M. Ramya
Precise localization of optic disc (OD) in color retinal images is an important sub-problem of automated retinal image analysis system. Drusen detection algorithms generally find lot of false positives at the OD region since the intensity of the drusen resembles with that of OD region. The exact identification an OD seems to be difficult as the disc boundaries are not clearly visible. Several parts of the disk is obscured by blood vessels. Further the size and position of the OD varies from one image to another. These factors make the OD detection a challenging task. In this paper we present a novel method to automatically detect the position of OD and eliminate it. The method starts with a color channel selection that provides a better contrast and reduces computational complexity. The contrast and the illumination of the image is normalized using adaptive histogram equalization (AHE) and homomorphic filtering respectively. The OD localization is then achieved by active contour segmentation using morphological operators. The algorithm is evaluated using 30 images. The proposed method was evaluated by comparing with conventional OD detection using a 2D circular Hough transform. The results prove an efficiency of the proposed method with an accuracy of 93%.
彩色视网膜图像视盘的精确定位是视网膜图像自动分析系统的一个重要子问题。由于Drusen的强度与OD区的强度相似,因此Drusen检测算法通常会在OD区发现大量的假阳性。确切的识别一个外径似乎是困难的,因为光盘边界不清楚可见。磁盘的几个部分被血管遮挡。此外,外径的大小和位置因图像而异。这些因素使得外径检测成为一项具有挑战性的任务。本文提出了一种自动检测外径位置并消除外径的新方法。该方法从颜色通道选择开始,以提供更好的对比度并降低计算复杂度。采用自适应直方图均衡化(AHE)和同态滤波分别对图像的对比度和照度进行归一化。然后利用形态学算子进行主动轮廓分割,实现OD定位。该算法使用30张图像进行评估。将该方法与传统的二维圆形霍夫变换外径检测方法进行了比较。结果证明了该方法的有效性,准确率达到93%。
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引用次数: 6
V2 Walk-Through a Stitched Image V2演练缝合图像
Pub Date : 2014-01-08 DOI: 10.1109/ICSIP.2014.42
G. Kiran, M. S.
In imaging devices, there is a trade-off between the images (snapshots) and video because of the limitation in storage capacity. Video clips need more storage space compared to images. This motivated to generate the video from a single stitched 2D image rather than storing video clips. Humans analyze varieties of cues from a single image and act accordingly, unlike robots. Creating a vertical virtual walk-through a Single stitched large sized image is proposed in two folds: In the first phase, the input images are stitched to form a single large sized image of a scene and in the second phase the virtual walk through the stitched image is rendered. The algorithm is tested on a set of nearly 400 images obtained from both indoor and outdoor scenes. The presented approach is computationally efficient and has been verified extensively by experiments. Since the proposed algorithm is completely automated it is amenable for implementation on robotic platforms.
在成像设备中,由于存储容量的限制,需要在图像(快照)和视频之间进行权衡。视频剪辑比图像需要更多的存储空间。这促使我们从单个拼接的2D图像中生成视频,而不是存储视频剪辑。与机器人不同,人类会从一张图像中分析各种各样的线索,并采取相应的行动。创建垂直虚拟行走通过一个单一的拼接大尺寸图像提出了两个折叠:在第一阶段,输入的图像被拼接形成一个单一的场景的大尺寸图像,在第二阶段,虚拟行走通过拼接图像被渲染。该算法在室内和室外场景的近400幅图像上进行了测试。该方法计算效率高,并得到了实验的广泛验证。由于所提出的算法是完全自动化的,因此可以在机器人平台上实现。
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引用次数: 1
Design and Analysis of High Speed Low Power Reusable on Chip Bus Based on Wishbone 基于Wishbone的高速低功耗复用芯片总线设计与分析
Pub Date : 2014-01-08 DOI: 10.1109/ICSIP.2014.37
Prashant Bachanna, Vivek Jalad, Sharanbasappa Shetkar
FPGA and ASIC design based on SoC technology have been widely used in the embedded systems. A flexible interconnection scheme is crucial in SoC design. In this paper, we adopt the Wishbone bus to interconnect a variety of devices due to its open architecture and many a free IP core with a Wishbone interface supplied by Open Cores organization. In general SoC system, a single bus interconnects all devices that are not divided into high-performance unit such as CPU, on-chip ram and low speed devices like uart, gpio and so on. It leads to a big problem: all Wishbone bus cycles run at the speed of the slowest device. We have to add the corresponding logic to regulate the system frequency for some low-speed devices, but it causes a new problem which increases the overall system power consumption. In view of the drawback, based on Wishbone bus, the paper proposes a double bus that makes first level Wishbone bus and the second level bus to interconnect the different devices according to the speed of the devices. Finally, we set up a SoC system to verify the performance of the proposed bus and the result shows that the double bus is feasible in low-power SoC design.
基于SoC技术的FPGA和ASIC设计在嵌入式系统中得到了广泛的应用。灵活的互连方案是SoC设计的关键。在本文中,我们采用Wishbone总线来互连各种设备,因为它的开放架构和许多免费的IP核与开放核心组织提供的Wishbone接口。在一般的SoC系统中,单个总线连接所有不分为高性能单元的设备,如CPU、片上ram和低速设备,如uart、gpio等。这导致了一个大问题:所有的Wishbone总线周期都以最慢的设备的速度运行。对于一些低速设备,我们不得不增加相应的逻辑来调节系统频率,但这又带来了一个新的问题,增加了系统的整体功耗。针对这一缺点,本文在Wishbone总线的基础上,提出了一种双层总线,即一级Wishbone总线和二级Wishbone总线,根据设备的速度将不同的设备互连起来。最后,我们建立了一个SoC系统来验证所提出的总线的性能,结果表明双总线在低功耗SoC设计中是可行的。
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引用次数: 4
A Survey of Resource Sharing Cloud Using Data Mining 基于数据挖掘的资源共享云研究综述
Pub Date : 2014-01-08 DOI: 10.1109/ICSIP.2014.57
D. Pratiba, G. Shobha
With the development of information technologies, Data Mining and Cloud Computing have been put forward and in wide search. Data Mining is defined as the process of analyzing data from different perspectives and summarizing it into useful information. It is also used for extracting the useful and potential information from the cloud. Most institutions and organizations have their own libraries and computer Servers, retrieving the data available in the above consortia is a difficult task. To overcome this, the resources can be shared using Data Mining and Cloud computing technology. Thus the end users would have access to all information.
随着信息技术的发展,数据挖掘和云计算被提出并得到了广泛的研究。数据挖掘被定义为从不同角度分析数据并将其总结为有用信息的过程。它还用于从云中提取有用的和潜在的信息。大多数机构和组织都有自己的图书馆和计算机服务器,检索上述联盟中可用的数据是一项艰巨的任务。为了克服这个问题,可以使用数据挖掘和云计算技术共享资源。因此,最终用户将能够访问所有信息。
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引用次数: 4
Blind Algorithm for Channel Length Estimation Using Cumulant Features 基于累积量特征的信道长度盲估计算法
Pub Date : 2014-01-08 DOI: 10.1109/ICSIP.2014.29
K. A. Babu, B. Ramkumar
Cognitive radios employed in emergency or military applications are subjected to harsh time varying channel conditions. In emergency application, since there is no information available about the wireless medium, blind equalizers are employed. One of the challenges in designing of blind equalizer is to choose the length of the equalizer. The length of the equalizer depends on the length of the channel which is generally not known. In this paper we propose a novel method to estimate the length of the channel using cumulant features. The validity of the proposed method is verified using computer simulation.
在紧急情况或军事应用中使用的认知无线电受到苛刻的时变信道条件的影响。在紧急应用中,由于没有关于无线介质的可用信息,因此采用盲均衡器。盲均衡器的设计难点之一是均衡器长度的选择。均衡器的长度取决于信道的长度,这通常是未知的。本文提出了一种利用累积量特征估计信道长度的新方法。通过计算机仿真验证了该方法的有效性。
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引用次数: 1
Euclidean Distance Based Offline Signature Recognition System Using Global and Local Wavelet Features 基于欧氏距离的全局和局部小波特征离线签名识别系统
Pub Date : 2014-01-08 DOI: 10.1109/ICSIP.2014.19
S. Angadi, Smita Gour
Signature recognition is an important requirement of automatic document verification system. Many approaches for signature recognition are found in literature. A novel approach for offline signature recognition system is presented in this paper, which is based on powerful global and local wavelet features (Energy features). The proposed system functions in three stages. Pre-processing stage, which consists of four steps: gray scale conversion, binarization, thinning and fitting boundary box in order to make signatures ready for feature extraction, Feature extraction stage, where totally 59 global and local wavelet based energy features are extracted which are used to distinguish the different signatures. Finally in classification stage, a simple Euclidean distance measure is used as decision tool. The average recognition accuracy obtained using this model ranges from 90% to 100% with the training set of 10 persons to 30 persons.
签名识别是文件自动验证系统的一个重要要求。文献中发现了许多签名识别的方法。本文提出了一种基于强大的全局和局部小波特征(能量特征)的离线签名识别方法。该系统的功能分为三个阶段。预处理阶段包括灰度转换、二值化、细化和拟合边界框四个步骤,为特征提取做好准备。特征提取阶段,提取59个基于小波的全局和局部能量特征,用于区分不同的特征。最后在分类阶段,使用简单的欧几里得距离度量作为决策工具。在10 ~ 30人的训练集上,使用该模型获得的平均识别准确率在90% ~ 100%之间。
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引用次数: 8
Discrete Wavelet Transform and Gradient Difference Based Approach for Text Localization in Videos 基于离散小波变换和梯度差分的视频文本定位方法
Pub Date : 2014-01-08 DOI: 10.1109/ICSIP.2014.50
B. H. Shekar, M. L.Smitha, P. Shivakumara
The text detection and localization is important for video analysis and understanding. The scene text in video contains semantic information and thus can contribute significantly to video retrieval and understanding. However, most of the approaches detect scene text in still images or single video frame. Videos differ from images in temporal redundancy. This paper proposes a novel hybrid method to robustly localize the texts in natural scene images and videos based on fusion of discrete wavelet transform and gradient difference. A set of rules and geometric properties have been devised to localize the actual text regions. Then, morphological operation is performed to generate the text regions and finally the connected component analysis is employed to localize the text in a video frame. The experimental results obtained on publicly available standard ICDAR 2003 and Hua dataset illustrate that the proposed method can accurately detect and localize texts of various sizes, fonts and colors. The experimentation on huge collection of video databases reveal the suitability of the proposed method to video databases.
文本检测和定位对于视频分析和理解具有重要意义。视频中的场景文本包含语义信息,对视频检索和理解具有重要意义。然而,大多数方法检测静态图像或单个视频帧中的场景文本。视频在时间冗余上不同于图像。提出了一种基于离散小波变换和梯度差分融合的自然场景图像和视频文本鲁棒定位方法。设计了一组规则和几何属性来定位实际的文本区域。然后进行形态学运算生成文本区域,最后利用连通分量分析对视频帧中的文本进行定位。在公开的标准ICDAR 2003和Hua数据集上的实验结果表明,该方法可以准确地检测和定位各种大小、字体和颜色的文本。在海量视频数据库上的实验表明了该方法对视频数据库的适用性。
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引用次数: 21
An Approach for Object Detection in Android Device 一种基于Android设备的目标检测方法
Pub Date : 2014-01-08 DOI: 10.1109/ICSIP.2014.6
G. Savitha, P. S. Venugopal, Sarojadevi, N. Chiplunkar
Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class in digital images and videos. An attempt is made in this study to detect and extract objects in an image implemented on android platform. Color images are converted to binary images using the thresholding technique. Morphological opening and closing filters are used in sequence for object detection. Contour based learning techniques are adopted for drawing contours of the objects detected. In the process objects are extracted and stored in an array for further analysis. OpenCV functions are used to implement these algorithms on android.
对象检测是一门与计算机视觉和图像处理相关的计算机技术,用于检测数字图像和视频中某一类语义对象的实例。本研究尝试在android平台上实现图像中的目标检测与提取。使用阈值分割技术将彩色图像转换为二值图像。形态学开闭滤波器依次用于目标检测。采用基于轮廓的学习技术绘制被检测物体的轮廓。在此过程中,对象被提取并存储在一个数组中以供进一步分析。OpenCV函数用于在android上实现这些算法。
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引用次数: 14
期刊
2014 Fifth International Conference on Signal and Image Processing
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