{"title":"A Fake Iris Detection Method Based on FFT and Quality Assessment","authors":"Xiaofu He, Yue Lu, P. Shi","doi":"10.1109/CCPR.2008.68","DOIUrl":"https://doi.org/10.1109/CCPR.2008.68","url":null,"abstract":"In recent years, iris recognition is becoming a very active topic in both research and practical applications. However, fake iris is a potential threat there are potential threats for iris-based systems. This paper presents a novel fake iris detection method based on the analysis of 2-D Fourier spectra together with iris image quality assessment. First, image quality assessment method is used to exclude the defocused, motion blurred fake iris. Then statistical properties of Fourier spectra for fake iris are used for clear fake iris detection. Experimental results show that the proposed method can detect photo iris and printed iris effectively.","PeriodicalId":292956,"journal":{"name":"2008 Chinese Conference on Pattern Recognition","volume":"16 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116720781","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}
{"title":"Image Classification Technology Based on Mining of Frequent Item Sets","authors":"Qing Nie, Shou-yi Zhan, Jing-Xia Su","doi":"10.1109/CCPR.2008.36","DOIUrl":"https://doi.org/10.1109/CCPR.2008.36","url":null,"abstract":"We propose a novel method to detect frequent and distinctive feature configuration on a class instance. Each neighborhood of a local feature is described by a list of nonzero indices, and generates a transaction. An efficient mining of frequent item sets algorithm is used to automatically find spatial configurations of local features occurring frequently on a class instance. These mined spatial configurations can be used as special words, incorporate into bag of features classification model. Through evaluation on PASCAL 2007 Visual Recognition Challenge dataset set, the test results show that this mining algorithm is computationally efficient and allows to process large training sets rapidly. Moreover, the mined feature configurations have higher discriminative power compare to individual features.","PeriodicalId":292956,"journal":{"name":"2008 Chinese Conference on Pattern Recognition","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126401985","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}
{"title":"Ensemble-Based Kernel Fisher Analysis for Face Recognition","authors":"Yafei Chen, Baochang Zhang","doi":"10.1109/CCPR.2008.59","DOIUrl":"https://doi.org/10.1109/CCPR.2008.59","url":null,"abstract":"This paper proposes an Ensemble-based kernel fisher analysis method for face recognition, which can effectively increase the performance of the histogram of gabor phase pattern (HGPP) method. The novelty of the paper lies in that it explains in theory why histogram can be combined with kernel fisher method, which the extended Chi-square similarity rules are positive definite. We then proposed the ensemble-based kernel fisher method to enhance the performance of HGPP, experiments on the large-scale FERET and CAS-PEAL database show that the proposed method gets much better recognition rates than the HGPP.","PeriodicalId":292956,"journal":{"name":"2008 Chinese Conference on Pattern Recognition","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125515875","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}
{"title":"GVF-Snake Based Method for Liver Region Segmentation","authors":"Linlin Huang, Tianyi Gui","doi":"10.1109/CCPR.2008.79","DOIUrl":"https://doi.org/10.1109/CCPR.2008.79","url":null,"abstract":"In this paper, we present a GVF-Snake based method for liver region segmentation on CT images. Firstly, the CT images are enhanced using a method of histogram equalization and anisotropic diffusion filter. Then, a region based method is applied to complement rough segmentation. Finally, an improved generalized gradient vector flow snake model (GVF-Snake) is adopted for the refinement of the rough segmentation. Experiment results show that the proposed method can precisely extract the liver region.","PeriodicalId":292956,"journal":{"name":"2008 Chinese Conference on Pattern Recognition","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121732269","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}
{"title":"A Video Text Location Method Based on Stroke Extraction and Conditional Morphology","authors":"Xiufei Wang, Lei Huang, Chang-ping Liu","doi":"10.1109/CCPR.2008.73","DOIUrl":"https://doi.org/10.1109/CCPR.2008.73","url":null,"abstract":"Texts in video frames are powerful sources of high-level semantics. They can be used for video analysis and content-based retrieving. Text location, which is the first and the most important step of text information extraction, affects the following recognition results considerably. In this paper, we strive to propose a text location method based on stroke extraction and conditional morphology. The stroke map of the input image is first got by a stroke extraction operator. Then, to remove the non-text disturbances in the stroke map, we introduce an improved method of morphology: conditional morphology. Compared with the original method, conditional morphology can not only remove the non-text noises but also enhance the text information, which improves the location performance remarkably. At last, the precise location of texts can be obtained by some merge-split rules with a combination of connected component analysis method. Experimental results show that our approach performs well with high speed and precision.","PeriodicalId":292956,"journal":{"name":"2008 Chinese Conference on Pattern Recognition","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123367520","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}
{"title":"Region-Based Color Fusion Method for Visible and IR Image Sequences","authors":"Bin Yang, Fengmei Sun, Shutao Li","doi":"10.1109/CCPR.2008.34","DOIUrl":"https://doi.org/10.1109/CCPR.2008.34","url":null,"abstract":"A novel region-based color mapping method is proposed to render fused image of visible and infrared (IR). The method is based on image segmentation, region recognition, image fusion and color transfer. Firstly visible image and IR image are fused based on the curvelet transform. At the same time, a color database is formed by grouping a set of natural color images according to their scene contents. A false color image obtained by assigning the source images to RGB channels is segmented with the multiscale normalized cuts method. Then each segmented region is recognized by support vector machine (SVM) and automatically associated with a natural color image. Finally the colors of the natural color image are transferred to the segmented region in a perceptually decorrelated color space. Experiments show that the image colorized by the proposed method resembles the natural color appearance and will help the observer interpreting the scene more intuitively than produced by other coloring methods.","PeriodicalId":292956,"journal":{"name":"2008 Chinese Conference on Pattern Recognition","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132108979","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}
{"title":"Study on the Quantitative Cytometry and Cervical Cancer Diagnosis Technology Based on Support Vector Machine","authors":"Duanquan Xu, Baochuan Pang","doi":"10.1109/CCPR.2008.80","DOIUrl":"https://doi.org/10.1109/CCPR.2008.80","url":null,"abstract":"The cervical cancer screening technology based on quantitative cytometry is studied. Feulgen stain is conducted on the sample of cervical tissues. Then the microscopic image of the sample is captured by CCD camera. The images of cell nucleuses are extracted by image segmentation. And the morphological, optical density and texture parameters of the cell nucleuses are calculated. The dimension of the feature parameter vectors is reduced using F-score and Random Forest algorithms. And the types of the cell nucleuses are identified by a SVM classifier. The diagnosis whether the carcinogenesis exists or not is given according to the distribution of DNA content of the epitheliums.","PeriodicalId":292956,"journal":{"name":"2008 Chinese Conference on Pattern Recognition","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123650373","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}
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
