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2009 IEEE International Conference on Signal and Image Processing Applications最新文献

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Enhanced image annotations based on spatial information extraction and ontologies 基于空间信息提取和本体的增强图像标注
2009 IEEE International Conference on Signal and Image Processing Applications Pub Date : 2009-11-18 DOI: 10.1109/ICSIPA.2009.5478621
Z. Muda, P. Lewis, T. Payne, M. Weal
{"title":"Enhanced image annotations based on spatial information extraction and ontologies","authors":"Z. Muda, P. Lewis, T. Payne, M. Weal","doi":"10.1109/ICSIPA.2009.5478621","DOIUrl":"https://doi.org/10.1109/ICSIPA.2009.5478621","url":null,"abstract":"Current research on image annotation often represents images in terms of labelled regions or objects, but pays little attention to the spatial positions or relationships between those regions or objects. To be effective, general purpose image retrieval systems require images with comprehensive annotations describing fully the content of the image. Much research is being done on automatic image annotation schemes but few authors address the issue of spatial annotations directly. This paper begins with a brief analysis of real picture queries to librarians showing how spatial terms are used to formulate queries. The paper is then concerned with the development of an enhanced automatic image annotation system, which extracts spatial information about objects in the image. The approach uses region boundaries and region labels to generate annotations describing absolute object positions and also relative positions between pairs of objects. A domain ontology and spatial information ontology are also used to extract more complex information about the relative closeness of objects to the viewer.","PeriodicalId":400165,"journal":{"name":"2009 IEEE International Conference on Signal and Image Processing Applications","volume":"2 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128905270","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: 11
1-D DCT shape feature for Image Retrieval 用于图像检索的一维DCT形状特征
2009 IEEE International Conference on Signal and Image Processing Applications Pub Date : 2009-11-18 DOI: 10.1109/ICSIPA.2009.5478692
S. Seyedin, M. F. A. Fauzi, F. M. Anuar
{"title":"1-D DCT shape feature for Image Retrieval","authors":"S. Seyedin, M. F. A. Fauzi, F. M. Anuar","doi":"10.1109/ICSIPA.2009.5478692","DOIUrl":"https://doi.org/10.1109/ICSIPA.2009.5478692","url":null,"abstract":"Content Based Image Retrieval (CBIR) is a difficult task. It needs different approaches and tools to get a set of images similar to a complex query image. Finding appropriate features is one of the important issues in this process. There are several tools to extract the appropriate features from the images. In this paper we explore the usage of 1-D Discrete Cosine Transform (DCT) as a tool for finding features of the boundary of objects in the query and database images. It is shown that the sensitivity of the DCT to rotation of objects can be reduced and the 1-D DCT of extended boundary signals can even give better results than the DFT in shape retrieval process.","PeriodicalId":400165,"journal":{"name":"2009 IEEE International Conference on Signal and Image Processing Applications","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132910504","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
Identification of vocal fold pathology based on Mel Frequency Band Energy Coefficients and singular value decomposition 基于Mel频带能量系数和奇异值分解的声带病理识别
2009 IEEE International Conference on Signal and Image Processing Applications Pub Date : 2009-11-18 DOI: 10.1109/ICSIPA.2009.5478710
M. Hariharan, M. Paulraj, S. Yaacob
{"title":"Identification of vocal fold pathology based on Mel Frequency Band Energy Coefficients and singular value decomposition","authors":"M. Hariharan, M. Paulraj, S. Yaacob","doi":"10.1109/ICSIPA.2009.5478710","DOIUrl":"https://doi.org/10.1109/ICSIPA.2009.5478710","url":null,"abstract":"Many approaches have been developed to detect the vocal fold pathology. Among the approaches, analysis of speech has proved to be an excellent tool for vocal fold pathology detection. This paper presents the Mel Frequency Band Energy Coefficients (MFBECs) combined with singular value decomposition (SVD) based feature extraction method for the classification of pathological or normal voice. In order to extract the most relevant information from the original MFBECs feature dataset, SVD is used. For the analysis, the speech samples of pathological and healthy subjects from the Massachusetts Eye and Ear Infirmary (MEEI) database are used. A simple k-means nearest neighbourhood (k-NN) and Linear Discriminant Analysis (LDA) based classifiers are used for testing the effectiveness of the MFBECs-SVD based feature vector. The experimental results show that the proposed features gives very promising classification accuracy and also can be effectively used to detect the pathological voices clinically.","PeriodicalId":400165,"journal":{"name":"2009 IEEE International Conference on Signal and Image Processing Applications","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128950943","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: 17
Adaptable models and semantic filtering for object recognition in street images 基于自适应模型和语义滤波的街道图像目标识别
2009 IEEE International Conference on Signal and Image Processing Applications Pub Date : 2009-11-18 DOI: 10.1109/ICSIPA.2009.5478683
Ge Qin, B. Vrusias
{"title":"Adaptable models and semantic filtering for object recognition in street images","authors":"Ge Qin, B. Vrusias","doi":"10.1109/ICSIPA.2009.5478683","DOIUrl":"https://doi.org/10.1109/ICSIPA.2009.5478683","url":null,"abstract":"The need for a generic and adaptable object detection and recognition method in images, is becoming a necessity today, given the rapid development of the internet and multimedia databases in general. This paper compares the state-of-the-art in object recognition and proposes a method based on adaptable models for detecting thematic categories of objects. Furthermore, automatically constructed semantics are used for filtering false positive objects. The classification of objects into categories is performed by the popular Adaboost. The method has been used for identifying car objects and so far has indicated not only accurate recognition performance, but also good adaptability to new objects types.","PeriodicalId":400165,"journal":{"name":"2009 IEEE International Conference on Signal and Image Processing Applications","volume":"195 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128358993","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
Color space selection for color image segmentation by spectral clustering 光谱聚类分割彩色图像的色彩空间选择
2009 IEEE International Conference on Signal and Image Processing Applications Pub Date : 2009-11-02 DOI: 10.1109/ICSIPA.2009.5478603
L. Busin, J. Shi, N. Vandenbroucke, L. Macaire
{"title":"Color space selection for color image segmentation by spectral clustering","authors":"L. Busin, J. Shi, N. Vandenbroucke, L. Macaire","doi":"10.1109/ICSIPA.2009.5478603","DOIUrl":"https://doi.org/10.1109/ICSIPA.2009.5478603","url":null,"abstract":"In this paper, we propose to segment color images by pixel clustering in a selected color space. This color space is selected among a set of classical color spaces according to a specific criterion based on a spectral clustering analysis. The clusters are determined by analyzing the 3D-histogram of the image coded in the selected color space thanks to a spectral clustering method. This scheme can identify clusters with complex shapes in the color space without any other post/pre-processing stages.","PeriodicalId":400165,"journal":{"name":"2009 IEEE International Conference on Signal and Image Processing Applications","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116290364","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: 23
Using neural network for liver detection in abdominal MRI images 利用神经网络对腹部MRI图像中的肝脏进行检测
2009 IEEE International Conference on Signal and Image Processing Applications Pub Date : 2009-11-01 DOI: 10.1109/ICSIPA.2009.5478613
A. Rafiee, H. Masoumi, A. Roosta
{"title":"Using neural network for liver detection in abdominal MRI images","authors":"A. Rafiee, H. Masoumi, A. Roosta","doi":"10.1109/ICSIPA.2009.5478613","DOIUrl":"https://doi.org/10.1109/ICSIPA.2009.5478613","url":null,"abstract":"MRI imaging is the one of useful abdominal imaging that the image parts are being demonstrated in high quality and clearness. Abdominal MRI images have been widely studied in the recent years as they are becoming an invaluable mean for abdominal organ investigation. In the field of medical image processing, some of the current interests are the automatic diagnosis of liver pathologies .The first and fundamental step in all these studies is the automatic liver segmentation that is still an open problem. In this paper we have presented new automatic system for liver segmentation from abdominal MRI images. This system includes two successive steps, pre-processing and liver image extraction algorithm. The pre-processing is applied for image enhancement (Edge preserved noise reduction) by using the mathematical morphology. After pre-processing, the abdominal MRI images are partitioned to some regions by using watershed algorithm. The feed forward neural network is used to liver features extraction in training stage. These features are used in liver recognition. Results show that this system recognizes the ridges of liver as well as physician liver extraction.","PeriodicalId":400165,"journal":{"name":"2009 IEEE International Conference on Signal and Image Processing Applications","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116901124","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: 17
Character recognition of the Batak Toba alphabet using signatures and simplified chain code 字符识别的巴塔克多巴字母使用签名和简化链码
2009 IEEE International Conference on Signal and Image Processing Applications Pub Date : 2009-11-01 DOI: 10.1109/ICSIPA.2009.5478614
Mauritz Panggabean, L. A. Rønningen
{"title":"Character recognition of the Batak Toba alphabet using signatures and simplified chain code","authors":"Mauritz Panggabean, L. A. Rønningen","doi":"10.1109/ICSIPA.2009.5478614","DOIUrl":"https://doi.org/10.1109/ICSIPA.2009.5478614","url":null,"abstract":"This paper presents the simplified chain code (SCC) from our concept of basic shape to recognize the characters of Batak Toba alphabet. The proposed chain code is based on the eight-direction Freeman chain code from which the horizontal and vertical directions are omitted. Hence we focus on shapes with dominant diagonal contours which characterize the recognized alphabet. Our implementation shows that recognizing the alphabet using the scale-invariant SCC can achieve more than 90% accuracy and is more than 10 times faster than that using signatures. To the best of our knowledge, this is the first reported attempt of recognizing the Batak Toba alphabet.","PeriodicalId":400165,"journal":{"name":"2009 IEEE International Conference on Signal and Image Processing Applications","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126136130","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
Automatic identification of needle's entrance point and angle in Vertebroplasty 椎体成形术中针入点及角度的自动识别
2009 IEEE International Conference on Signal and Image Processing Applications Pub Date : 2009-11-01 DOI: 10.1109/ICSIPA.2009.5478633
Sara Mardani Samani, M. Yazdi, M. Hadi Bagheri
{"title":"Automatic identification of needle's entrance point and angle in Vertebroplasty","authors":"Sara Mardani Samani, M. Yazdi, M. Hadi Bagheri","doi":"10.1109/ICSIPA.2009.5478633","DOIUrl":"https://doi.org/10.1109/ICSIPA.2009.5478633","url":null,"abstract":"Vertebral compression fracture (VCF) is a disease which affects the body of vertebrae usually due to osteoporosis or trauma. Vertebroplasty is a common therapeutic procedure to treat VCF. In Vertebroplasty, bone cement is injected into the body of fractured vertebra through the hollow needle via skin path. To do this, physicians insert the needle into the body experimentally guided by medical images. Proper and precise needle insertion is mandatory to avoid damage of sensitive structures such as spinal cord or nerve roots. In this paper, we propose an automatic approach to detect the needle's entrance point and its 3D direction using only the CT images of the patient. The results obtained by our approach have been validated by specialists and the approach can be used clinically.","PeriodicalId":400165,"journal":{"name":"2009 IEEE International Conference on Signal and Image Processing Applications","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114936889","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
An improved quantization based watermarking scheme using local entropy in wavelet domain 一种改进的基于小波域局部熵的量化水印方案
2009 IEEE International Conference on Signal and Image Processing Applications Pub Date : 2009-11-01 DOI: 10.1109/ICSIPA.2009.5478604
M. Boroumand, A. Ebrahimi
{"title":"An improved quantization based watermarking scheme using local entropy in wavelet domain","authors":"M. Boroumand, A. Ebrahimi","doi":"10.1109/ICSIPA.2009.5478604","DOIUrl":"https://doi.org/10.1109/ICSIPA.2009.5478604","url":null,"abstract":"This paper presents a method for robust watermarking of digital images in wavelet domain. A new HVS model which uses local entropy in addition to conventional masking characteristics of the human visual system such as frequency, luminance and contrast masking has been utilized to increase the robustness of the scheme. Experimental results demonstrate the superiority of the proposed method over the similar method in terms of robustness and transparency.","PeriodicalId":400165,"journal":{"name":"2009 IEEE International Conference on Signal and Image Processing Applications","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129870431","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: 5
Enhancing text image binarization using 3D tensor voting 利用三维张量投票增强文本图像二值化
2009 IEEE International Conference on Signal and Image Processing Applications Pub Date : 2009-11-01 DOI: 10.1109/ICSIPA.2009.5478607
T. Dinh, Jonghyun Park, Gueesang Lee
{"title":"Enhancing text image binarization using 3D tensor voting","authors":"T. Dinh, Jonghyun Park, Gueesang Lee","doi":"10.1109/ICSIPA.2009.5478607","DOIUrl":"https://doi.org/10.1109/ICSIPA.2009.5478607","url":null,"abstract":"Text image binarization is an important step in text image analysis and text understanding systems. Some corrupted regions may remain in the binarization result due to noises such as dust, streaks, shadows and small unwanted objects. In this paper, a novel method based on 3D tensor voting is proposed for enhancing text image binarization. The 3D tensor voting is used to detect corrupted regions by analysing surfaces of text stroke and background in a binary image. Our method is effective on binary images having gaps in text stroke or noise regions in background.","PeriodicalId":400165,"journal":{"name":"2009 IEEE International Conference on Signal and Image Processing Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128404127","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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