2011 International Conference on Image Information Processing最新文献_第8页

Comparative study of Directional antenna gain for MANET Nodes and Cluster Head Gateway in Integrated Mobile Adhoc Network 综合移动自组网中MANET节点和簇头网关定向天线增益的比较研究

2011 International Conference on Image Information Processing Pub Date : 2011-12-22 DOI: 10.1109/ICIIP.2011.6108895

A. Bagwari, R. Jee, Rahul Tiwari, Ashish Kumar

引用次数: 0

Robust binarization of degraded documents using adaptive-cum-interpolative thresholding in a multi-scale framework 在多尺度框架下使用自适应插值阈值对退化文档进行鲁棒二值化

2011 International Conference on Image Information Processing Pub Date : 2011-12-22 DOI: 10.1109/ICIIP.2011.6108912

Soumen Bag, Partha Bhowmick, P. Behera, Gaurav Harit

{"title":"Robust binarization of degraded documents using adaptive-cum-interpolative thresholding in a multi-scale framework","authors":"Soumen Bag, Partha Bhowmick, P. Behera, Gaurav Harit","doi":"10.1109/ICIIP.2011.6108912","DOIUrl":"https://doi.org/10.1109/ICIIP.2011.6108912","url":null,"abstract":"A novel technique for binarization of degraded documents is proposed. It works in a multi-scale framework with an adaptive-cum-interpolative thresholding as a modification of Otsu's method. Instead of computing a global threshold value for an input document image, it computes the local threshold values for a small set of grid points by observing the intensity pattern of the pixels lying in the concerned grid cells. Thresholds estimated for these grid points are used, in turn, to compute the threshold values of all the remaining pixels using a fast-yet-efficient interpolation procedure. To handle noises in degraded images, this grid-based adaptive thresholding is applied in successively reducing scales to obtain the nearoptimal binarization as a set of connected components. After a post-processing with these connected components, we get the final output. Exhaustive experimentation has been carried out with benchmark datasets including George Washington corpus of handwritten documents, and also with our own datasets. When compared to other methods, the proposed method is found to be robust and appreciably better, as tested by conventional evaluation schemes.","PeriodicalId":201779,"journal":{"name":"2011 International Conference on Image Information Processing","volume":"31 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":"126994887","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

Wrapper based feature selection in hyperspectral image data using self-adaptive differential evolution 基于自适应差分进化的高光谱图像数据包装特征选择

2011 International Conference on Image Information Processing Pub Date : 2011-12-22 DOI: 10.1109/ICIIP.2011.6108919

Aloke Datta, Susmita K. Ghosh, Asish Ghosh

{"title":"Wrapper based feature selection in hyperspectral image data using self-adaptive differential evolution","authors":"Aloke Datta, Susmita K. Ghosh, Asish Ghosh","doi":"10.1109/ICIIP.2011.6108919","DOIUrl":"https://doi.org/10.1109/ICIIP.2011.6108919","url":null,"abstract":"Hyperspectral sensors acquire a set of images from hundreds of narrow and contiguous bands of electromagnetic spectrum from visible to infrared regions. The computational complexity is very high for classification of hyperspectral images due to the presence of large number of bands. In such a scenario, feature selection is very essential technique for reducing the dimensionality. In the proposed work, an attempt has been made to develop a feature selection technique based on evolutionary approach. Self-adaptive differential evolution (SADE) is used for searching feature subset. In SADE, the parameter values adapt themselves with generation to generation. Proposed method follows wrapper model for subset evaluation. Fuzzy kNN classifier is incorporated to calculate the classification accuracy which is used as evaluation criterion. The proposed methodology also includes a feature estimating technique, called ReliefF method, for removing the redundant feature. To demonstrate the effectiveness of the proposed method, results are compared with differential evolution based, genetic algorithm based and ant colony optimization based feature selection techniques. This method achieves very promising results compared to others in terms of overall classification accuracy and Kappa coefficient.","PeriodicalId":201779,"journal":{"name":"2011 International Conference on Image Information Processing","volume":"20 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":"116960579","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

Face recognition using multimodal biometric features 基于多模态生物特征的人脸识别

2011 International Conference on Image Information Processing Pub Date : 2011-12-22 DOI: 10.1109/ICIIP.2011.6108945

N. Lakshmiprabha, J. Bhattacharya, S. Majumder

引用次数: 45

On the implementation of a information hiding design based on saliency map 基于显著性映射的信息隐藏设计的实现

2011 International Conference on Image Information Processing Pub Date : 2011-12-22 DOI: 10.1109/ICIIP.2011.6108926

A. Basu, T. S. Das, S. Sarkar, Swanirbhar Majumder

引用次数: 5

A N8(P) detail preserving adaptive filter for impulse noise removal 一个N8(P)细节保持自适应滤波器用于脉冲噪声去除

2011 International Conference on Image Information Processing Pub Date : 2011-12-22 DOI: 10.1109/ICIIP.2011.6108865

K. K. Singh, K. Pal, A. Mehrotra, M. Nigam

引用次数: 9

Road extraction using K-Means clustering and morphological operations 基于K-Means聚类和形态操作的道路提取

2011 International Conference on Image Information Processing Pub Date : 2011-12-22 DOI: 10.1109/ICIIP.2011.6108839

R. Maurya, P. Gupta, A. S. Shukla

引用次数: 64

PROSOPON: A virtual anatomical 3D head model PROSOPON:一个虚拟的三维头部解剖模型

2011 International Conference on Image Information Processing Pub Date : 2011-12-22 DOI: 10.1109/ICIIP.2011.6108931

Christos Sagonas, I. Pitas, A. Kirgidis, K. Lyroudia

引用次数: 1

Automated ovarian follicle recognition for Polycystic Ovary Syndrome 多囊卵巢综合征的自动卵泡识别

2011 International Conference on Image Information Processing Pub Date : 2011-12-22 DOI: 10.1109/ICIIP.2011.6108968

Palak Mehrotra, C. Chakraborty, Biswanath Ghoshdastidar, S. Ghoshdastidar, Kakoli Ghoshdastidar

{"title":"Automated ovarian follicle recognition for Polycystic Ovary Syndrome","authors":"Palak Mehrotra, C. Chakraborty, Biswanath Ghoshdastidar, S. Ghoshdastidar, Kakoli Ghoshdastidar","doi":"10.1109/ICIIP.2011.6108968","DOIUrl":"https://doi.org/10.1109/ICIIP.2011.6108968","url":null,"abstract":"Polycystic Ovary Syndrome (PCOS) is a complex endocrine disorder affecting many women in the pubertal as well as reproductive age groups with profound adverse affects such as obesity, infertility, cardiovascular disease and diabetes mellitus. Diagnosis of the condition is by clinical, biochemical and imaging parameters. The principle feature on ultrasound is the presence of polycystic ovaries with peripheral arranged cysts and dense stroma. During ultrasound evaluation due to overlapping of the follicles as well as inherent noise of the equipment delineating, making this characteristic appearance may sometimes become challenging, making diagnosis time consuming. Moreover the interpretation would vary considerably from one operator to another as it is largely an experience dependent procedure. In this paper an automated scheme for the detection of this pathognomonic pattern and arrangement of follicles is proposed to overcome this problem. Firstly the input ultrasound image was preprocessed by multiscale morphological approach for contrast enhancement. Then a scanline thresholding is used to extract the contours of the follicles. The results are compared with the results obtained by manual selection to verify the effectivity of scheme.","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":"128277712","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: 29

A new algorithm for 3D object representation and its application for human face verification 一种新的三维物体表示算法及其在人脸识别中的应用

2011 International Conference on Image Information Processing Pub Date : 2011-12-22 DOI: 10.1109/ICIIP.2011.6108970

P. Dhane, Ankita Jain, K. Kutty

{"title":"A new algorithm for 3D object representation and its application for human face verification","authors":"P. Dhane, Ankita Jain, K. Kutty","doi":"10.1109/ICIIP.2011.6108970","DOIUrl":"https://doi.org/10.1109/ICIIP.2011.6108970","url":null,"abstract":"There are many papers published on the use of 2D images for object representation. The fundamental issue with these approaches lies in the fact that a conventional image maps 3D real world objects into a 2D plane. This causes loss of 3D information - which means loss of 3D features as well for further analysis. There have been attempts using 3D and 2.5D scanners in order to access range data from objects for further analysis. However, these systems require special scanners and associated hardware, and many a times the complete information that is obtained from such systems is not required for further analysis. In this paper, we propose a simple system that projects a light beam over an object of interest and using a simple optical camera a video is recorded. This enables us to have 2D data as acquired from the camera along with the 3D data that is derived out of the deviations in the scan pattern because of the non-planarity of the object of interest. We have limited our research to using 3D features only for object representation and extended the same logic for face verification. The results that we have obtained show that in spite of using only 3D features, the system is able to verify faces with varied expressions correctly on 75% of the test data. The system is robust to slight tilt in head angle and normal human expressions like smile, frown, grin etc.","PeriodicalId":201779,"journal":{"name":"2011 International Conference on Image Information Processing","volume":"50 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":"127442630","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