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2011 International Conference on Image Information Processing最新文献

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Newborn's ear recognition: Can it be done? 新生儿的耳朵识别:能做到吗?
2011 International Conference on Image Information Processing Pub Date : 2011-12-22 DOI: 10.1109/ICIIP.2011.6108944
S. Tiwari, Aruni Singh, S. Singh
{"title":"Newborn's ear recognition: Can it be done?","authors":"S. Tiwari, Aruni Singh, S. Singh","doi":"10.1109/ICIIP.2011.6108944","DOIUrl":"https://doi.org/10.1109/ICIIP.2011.6108944","url":null,"abstract":"Abduction, swapping and mix ups are the unfortunate events that could happen to infants while in hospital premises and medical personnel are finding it difficult to curb this unfortunate incidents. Existing biometric and non biometric methods fail to provide enough level of security and research done to solve this problem is minimal. This paper introduces the concept of using ear recognition for identification of newborn and presents automatic ear recognition algorithm. The main contribution of this research is (i) preparation of a new born ear database of 210 individuals with slight variations in illumination and pose (ii) testing of different ear matching algorithms. On an ear biometric database of 210 infants it is concluded that ear can be used as biometric feature to identify the newborn.","PeriodicalId":201779,"journal":{"name":"2011 International Conference on Image Information Processing","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126326083","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: 25
Recognition of Bangla text from scene images through perspective correction 通过透视校正从场景图像中识别孟加拉语文本
2011 International Conference on Image Information Processing Pub Date : 2011-12-22 DOI: 10.1109/ICIIP.2011.6108886
R. Ghoshal, A. Roy, S. Parui
{"title":"Recognition of Bangla text from scene images through perspective correction","authors":"R. Ghoshal, A. Roy, S. Parui","doi":"10.1109/ICIIP.2011.6108886","DOIUrl":"https://doi.org/10.1109/ICIIP.2011.6108886","url":null,"abstract":"This article proposes a scheme for automatic extraction and recognition of Bangla text from natural scene images. An image, when captured by a digital camera may have perspective distortion. Before extracting text symbols, this distortion is corrected using Homography transform. For text extraction, headlines are detected using morphology. First, the components attached or close to the detected headlines, are separated. Further, by applying certain shape and position based conditions we could distinguish text and non-text. Afterwards, by removing the headline we partition the text into two different zones. For recognition purpose, the local chain code histograms of input character are used as features. Finally, separate Multilayer perceptrons (MLPs) are used to recognize text symbols reside in different zones. The classifiers are trained using about 7500 samples of 53 classes. We tested our algorithm on 100 scene images.","PeriodicalId":201779,"journal":{"name":"2011 International Conference on Image Information Processing","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127957889","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: 14
Analysis of training parameters for classifiers based on Haar-like features to detect human faces 基于haar特征的人脸识别分类器训练参数分析
2011 International Conference on Image Information Processing Pub Date : 2011-12-22 DOI: 10.1109/ICIIP.2011.6108889
Supratim Gupta, A. Dasgupta, A. Routray
{"title":"Analysis of training parameters for classifiers based on Haar-like features to detect human faces","authors":"Supratim Gupta, A. Dasgupta, A. Routray","doi":"10.1109/ICIIP.2011.6108889","DOIUrl":"https://doi.org/10.1109/ICIIP.2011.6108889","url":null,"abstract":"This paper analyzes the performance of the Haar-like feature based classifier for detection of face with fewer features. The lower dimensional feature space representation of the image may reduce the computational burden compromising the accuracy in detection of faces with varying orientations. In this work we train the classifier with positive instances of different orientations under such feature constraint. The training parameters like maximum deviation and maximum angle are varied to form different classifiers. Experimental results show optimum values of the design parameters can produce good performance of the classifier to detect frontal as well as tilted human faces.","PeriodicalId":201779,"journal":{"name":"2011 International Conference on Image Information Processing","volume":"352 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115979579","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
Fusion of multimodality Medical Images using combined Activity Level Measurement and Contourlet Transform 结合活动水平测量和Contourlet变换的多模态医学图像融合
2011 International Conference on Image Information Processing Pub Date : 2011-12-22 DOI: 10.1109/ICIIP.2011.6108896
Sudeb Das, M. Kundu
{"title":"Fusion of multimodality Medical Images using combined Activity Level Measurement and Contourlet Transform","authors":"Sudeb Das, M. Kundu","doi":"10.1109/ICIIP.2011.6108896","DOIUrl":"https://doi.org/10.1109/ICIIP.2011.6108896","url":null,"abstract":"In this paper, we propose a novel multimodality Medical Image Fusion (MIF) method, based on a novel combined Activity Level Measurement (ALM) and Contourlet Transform (CNT) for spatially registered, multi-sensor, multi-resolution medical images. The source medical images are first decomposed by CNT. The low-frequency subbands (LFSs) are fused using the novel combined ALM, and the high-frequency subbands (HFSs) are fused according to their ‘local average energy’ of the neighborhood of coefficients. Then inverse contourlet transform (ICNT) is applied to the fused coefficients to get the fused image. The performance of the proposed scheme is evaluated by various quantitative measures like Mutual Information (MI), Spatial Frequency (SF), and Entropy (EN) etc. Visual and quantitative analysis and comparisons show the effectiveness of the proposed scheme in fusing multimodality medical images.","PeriodicalId":201779,"journal":{"name":"2011 International Conference on Image Information Processing","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134101719","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: 12
Optimum band selection in hyperspectral imagery using swarm intelligence optimization algorithms 基于群智能优化算法的高光谱图像波段优选
2011 International Conference on Image Information Processing Pub Date : 2011-12-22 DOI: 10.1109/ICIIP.2011.6108925
F. Samadzadegan, F. Mahmoudi
{"title":"Optimum band selection in hyperspectral imagery using swarm intelligence optimization algorithms","authors":"F. Samadzadegan, F. Mahmoudi","doi":"10.1109/ICIIP.2011.6108925","DOIUrl":"https://doi.org/10.1109/ICIIP.2011.6108925","url":null,"abstract":"Despite rich and fine spectral information of hyperspectral imagery, curse of dimensionality and Hughes phenomenon affect the land use/cover classification accuracy of such images. In this situation, optimal feature/band selection based on optimization procedures has high potential to improve the accuracy of hyperspectral image pattern recognition and classification. Among other optimization techniques, Meta heuristic optimization algorithms such as Swarm intelligence-based methods are so capable in solving feature/band selection problems. This paper evaluates the potential of Firefly algorithm (FA) and Particle Swarm Optimization (PSO) as representatives of swarm intelligence-based methodologies in optimal band selection and dimensionality reduction of hyperspectral imagery. Implementation results of Firefly algorithm and PSO in the case of AVIRIS hyperspectral image classification is compared with Genetic algorithm as another well known Meta heuristic optimization method. The preliminarily results confirm the high capabilities of Firefly algorithm and PSO for solving optimal feature/band subset selection.","PeriodicalId":201779,"journal":{"name":"2011 International Conference on Image Information Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131723606","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: 10
Enhancing information retrieval efficiency using semantic-based-combined-similarity-measure 利用基于语义的组合相似度测度提高信息检索效率
2011 International Conference on Image Information Processing Pub Date : 2011-12-22 DOI: 10.1109/ICIIP.2011.6108982
Mayank Saini, Dharmendar Sharma, P. Gupta
{"title":"Enhancing information retrieval efficiency using semantic-based-combined-similarity-measure","authors":"Mayank Saini, Dharmendar Sharma, P. Gupta","doi":"10.1109/ICIIP.2011.6108982","DOIUrl":"https://doi.org/10.1109/ICIIP.2011.6108982","url":null,"abstract":"Most of the knowledge intensive organizations are having their information resided in large text document repositories and most of these text repositories and databases are either unstructured or semi-structured. Recently various soft computing techniques have been used to improve information retrieval efficiency. More specifically genetic algorithms have been used for various information retrieval components like matching function learning, documents clustering, information extraction, query optimization [1 – 6]. In most of the cases in information retrieval matching function is based on term frequency. But the problem with this approach is that the syntactic information of the text document is lost and phrases are also not considered, so results in poor accuracy. In this paper we have proposed a new semantic based similarity measure in which each term can be a phrase or a single word and the weight assigned to each term is based on its semantic importance considering each sentence. We have used this semantic similarity measure along with other standard similarity measure as Jaccard and cosine to form the semantic-based-combined-similarity-measure. Standard genetic algorithm has been used to optimize the weight given for each similarity measure.","PeriodicalId":201779,"journal":{"name":"2011 International Conference on Image Information Processing","volume":"138 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132688870","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: 22
Random automatic detection of clusters 随机自动检测集群
2011 International Conference on Image Information Processing Pub Date : 2011-12-22 DOI: 10.1109/ICIIP.2011.6108856
Mamta Mittal, V.P. Singh, Sharma R. K.
{"title":"Random automatic detection of clusters","authors":"Mamta Mittal, V.P. Singh, Sharma R. K.","doi":"10.1109/ICIIP.2011.6108856","DOIUrl":"https://doi.org/10.1109/ICIIP.2011.6108856","url":null,"abstract":"Clustering is a way to partition the database in various groups. It is being used in data mining at a very large scale. There are different clustering methods but the focus in this paper is on partitioning based clustering. In literature many algorithm including k-Means are available that require prior information from the outside world about the number of clusters into which the database is to be divided. However, now days a database requires such algorithms that can generate different clusters automatically and moreover at each run the database requires to be partitioned into different number of clusters as well as different shape and size of grouping. In this paper a new partitioning based clustering algorithm that can generate clusters automatically without any previous knowledge on the user side has been proposed. The clusters so generated may not only differ in number but also will be of different shape and size.","PeriodicalId":201779,"journal":{"name":"2011 International Conference on Image Information Processing","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124374965","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
Handwritten Bangla character recognition in machine-printed forms using gradient information and Haar wavelet 基于梯度信息和Haar小波的机印孟加拉手写体字符识别
2011 International Conference on Image Information Processing Pub Date : 2011-12-22 DOI: 10.1109/ICIIP.2011.6108911
Sekhar Mandal, Sanjib Sur, Avishek Dan, Partha Bhowmick
{"title":"Handwritten Bangla character recognition in machine-printed forms using gradient information and Haar wavelet","authors":"Sekhar Mandal, Sanjib Sur, Avishek Dan, Partha Bhowmick","doi":"10.1109/ICIIP.2011.6108911","DOIUrl":"https://doi.org/10.1109/ICIIP.2011.6108911","url":null,"abstract":"A robust and efficient algorithm to recognize handwritten Bangla (Bengali) characters in machine-printed forms is proposed. It is based on the combination of gradient features and Haar wavelet coefficients. The gradient feature is used to capture local characteristics, and for its sensitivity to the usual deformation and idiosyncrasy of handwritten characters, wavelet transform is used for multi-resolution analysis of character images. Such a strategy with combined features captures adequate global characteristics in different scales. Two feature-combination schemes are devised and tested on test images of 4372 instances of 49 characters and 10 numerals, after being trained by a set of 59×25 = 1475 images. Finally, a k-NN classifier is used for the character recognition, which shows 87.65% and 88.95% recognition accuracies for the two schemes.","PeriodicalId":201779,"journal":{"name":"2011 International Conference on Image Information Processing","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115037455","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: 22
Object-based image fusion for minimization of color distortion in high-resolution satellite imagery 基于目标的图像融合在高分辨率卫星图像中实现颜色失真最小化
2011 International Conference on Image Information Processing Pub Date : 2011-12-22 DOI: 10.1109/ICIIP.2011.6108861
Munmun Baisantry, D. Negi, O. P. Manocha, Bhanu Pratap Singh, Sandeep Kishore
{"title":"Object-based image fusion for minimization of color distortion in high-resolution satellite imagery","authors":"Munmun Baisantry, D. Negi, O. P. Manocha, Bhanu Pratap Singh, Sandeep Kishore","doi":"10.1109/ICIIP.2011.6108861","DOIUrl":"https://doi.org/10.1109/ICIIP.2011.6108861","url":null,"abstract":"Color or spectral distortion is a serious issue in the field of Image Fusion. The problem is more prevalent in high-resolution satellite imagery due to spectral mismatching of panchromatic and MS bands. Current pixel-based techniques are not well-equipped to handle the problem. Moreover, these techniques do not consider the spatial, spectral or radiometric characteristics of various objects in the image and all the pixels are fused with the same criterion. To bring the application closer to the real-world scene, a more realistic, self-adjustable, attribute-based object-oriented paradigm towards fusion has been proposed in the paper. Various objects attributes have been considered at different levels to embed greater spatial details into the low resolution MSS image with minimum spectral distortion. Quantitative assessment indices have also been calculated to prove that our method is superior in terms of minimization of color distortion and maximization of spatial details as compared to other methods.","PeriodicalId":201779,"journal":{"name":"2011 International Conference on Image Information Processing","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116311119","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
New Accordion based video compression approach 新的基于手风琴的视频压缩方法
2011 International Conference on Image Information Processing Pub Date : 2011-12-22 DOI: 10.1109/ICIIP.2011.6108867
T. Ouni, M. Abid
{"title":"New Accordion based video compression approach","authors":"T. Ouni, M. Abid","doi":"10.1109/ICIIP.2011.6108867","DOIUrl":"https://doi.org/10.1109/ICIIP.2011.6108867","url":null,"abstract":"In this paper, we propose a new approach based on the accordion transform that tends to exploit the both intra and inter frame correlation. The major novelty of the new approach compared to classic one is the dynamic strategy of video frames scan. The direction of the frames scan will depends on a gradient based algorithm which tries to predict the direction where minimal pixels intensities changes are recorded. Both objective (PSNR) and subjective quality evaluation prove the improvement of the compression efficiency, especially in fast and uniform motion video sequences which usually represents the weakness of the classical approach.","PeriodicalId":201779,"journal":{"name":"2011 International Conference on Image Information Processing","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123589360","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
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