2009 IEEE Symposium on Computational Intelligence for Image Processing最新文献

Determination of the essential matrix using discrete and differential matching constraints 用离散和微分匹配约束确定基本矩阵

2009 IEEE Symposium on Computational Intelligence for Image Processing Pub Date : 2009-05-15 DOI: 10.1109/CIIP.2009.4937889

Adel H. Fakih, J. Zelek

引用次数: 0

OWA filters: A robust filtering method and its application to color images OWA滤波器:一种鲁棒滤波方法及其在彩色图像中的应用

2009 IEEE Symposium on Computational Intelligence for Image Processing Pub Date : 2009-05-15 DOI: 10.1109/CIIP.2009.4937873

Aryabrata Basu, M. Nachtegael

{"title":"OWA filters: A robust filtering method and its application to color images","authors":"Aryabrata Basu, M. Nachtegael","doi":"10.1109/CIIP.2009.4937873","DOIUrl":"https://doi.org/10.1109/CIIP.2009.4937873","url":null,"abstract":"Bilateral filtering provides a scheme for non-iterative edge-preserving smoothing, but the results could be strongly affected by the presence of outliers. In this paper we develop a robust bilateral filter for color images, and in order to achieve this we propose to improve the bilateral filtering technique [13] by using Ordered Weighted Averaging operators. We adopt a fuzzy logic based approach: if the filtering is considered as a weighted averaging, then each filter is associated with a fuzzy set and the membership values of these fuzzy sets represent the weights. In this context, the bilateral filter is a conjunction of two fuzzy sets in the case of grayscale images: one in the spatial domain and one in a photometric domain. Applied to color images, we propose to extend the conjunction to three fuzzy sets: one in the spatial domain, one in the brightness domain and one in the chromatic domain. Taking into account the robustness of rank filters, we propose to define an OWA filter in order to obtain robust adaptive filters in brightness and chromaticity. The robustness and performance of the filter is illustrated with several experiments, revealing its ability to remove different types of noise in the presence of outliers, while preserving edges. The noise types considered are impulse noise and a combination of Gaussian noise with “salt and pepper” noise types.","PeriodicalId":349149,"journal":{"name":"2009 IEEE Symposium on Computational Intelligence for Image Processing","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126199661","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

Metric planar rectification from perspective view via circles 从透视角度通过圆进行公制平面整流

2009 IEEE Symposium on Computational Intelligence for Image Processing Pub Date : 2009-05-15 DOI: 10.1109/CIIP.2009.4937883

Yisong Chen, Peng Lu, WenHang Li, ShaoRong Wang

引用次数: 1

A new approach to image sparse decomposition based on MP 基于MP的图像稀疏分解新方法

2009 IEEE Symposium on Computational Intelligence for Image Processing Pub Date : 2009-05-15 DOI: 10.1109/CIIP.2009.4937882

Yingyun Yang, Dongxin Shi, Ke Sun, Qin Zhang

引用次数: 0

2D ultrasound image segmentation using graph cuts and local image features 基于图切割和局部图像特征的二维超声图像分割

2009 IEEE Symposium on Computational Intelligence for Image Processing Pub Date : 2009-05-15 DOI: 10.1109/CIIP.2009.4937877

M. Zouqi, J. Samarabandu

引用次数: 11

An efficient architecture for hardware implementations of image processing algorithms 一种高效的图像处理算法硬件实现架构

2009 IEEE Symposium on Computational Intelligence for Image Processing Pub Date : 2009-05-15 DOI: 10.1109/CIIP.2009.4937875

F. Khalvati, H. Tizhoosh

引用次数: 2

A modified fuzzy c-means algorithm with adaptive spatial information for color image segmentation 一种自适应空间信息的改进模糊c均值算法用于彩色图像分割

2009 IEEE Symposium on Computational Intelligence for Image Processing Pub Date : 2009-05-15 DOI: 10.1109/CIIP.2009.4937879

Zhiding Yu, R. Zou, Simin Yu

{"title":"A modified fuzzy c-means algorithm with adaptive spatial information for color image segmentation","authors":"Zhiding Yu, R. Zou, Simin Yu","doi":"10.1109/CIIP.2009.4937879","DOIUrl":"https://doi.org/10.1109/CIIP.2009.4937879","url":null,"abstract":"Though FCM has long been widely used in image segmentation, it yet faces several challenges. Traditional FCM needs a laborious process to decide cluster center number by repetitive tests. Moreover, random initialization of cluster centers can let the algorithm easily fall onto local minimum, causing the segmentation results to be suboptimal. Traditional FCM is also sensitive to noise due to the reason that the pixel partitioning process goes completely in the feature space, ignoring some necessary spatial information. In this paper we introduce a modified FCM algorithm for color image segmentation. The proposed algorithm adopts an adaptive and robust initialization method which automatically decides initial cluster center values and center number according to the input image. In addition, by deciding the window size of pixel neighbor and the weights of neighbor memberships according to local color variance, the proposed approach adaptively incorporates spatial information to the clustering process and increases the algorithm robustness to noise pixels and drastic color variance. Experimental results have shown the superiority of modified FCM over traditional FCM algorithm.","PeriodicalId":349149,"journal":{"name":"2009 IEEE Symposium on Computational Intelligence for Image Processing","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124799303","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

Compressed sensing for face recognition 压缩感知用于人脸识别

2009 IEEE Symposium on Computational Intelligence for Image Processing Pub Date : 2009-05-15 DOI: 10.1109/CIIP.2009.4937888

N. Vo, D. Vo, S. Challa, W. Moran

引用次数: 12

3-D reconstruction and automatic fusion of edge maps from different modalities of an object 三维重建和自动融合边缘地图从不同形态的对象

2009 IEEE Symposium on Computational Intelligence for Image Processing Pub Date : 2009-05-15 DOI: 10.1109/CIIP.2009.4937880

U. C. Pati, Aditya Modi, P. Dutta, A. Barua

{"title":"3-D reconstruction and automatic fusion of edge maps from different modalities of an object","authors":"U. C. Pati, Aditya Modi, P. Dutta, A. Barua","doi":"10.1109/CIIP.2009.4937880","DOIUrl":"https://doi.org/10.1109/CIIP.2009.4937880","url":null,"abstract":"The paper presents reconstruction of a 3-D model as well as automatic fusion of edge maps extracted from the 3-D model and intensity image of an object. A data acquisition system has been developed with a laser source and camera. The 3-D model of the object is reconstructed by registration and integration of a set of range images obtained from scanning the object by laser beam. The intensity image of the object is captured under illumination light. Edge maps in both the cases are extracted by appropriate techniques. The corner points of various shapes in both the edge maps are obtained by implementing a technique using shape signatures. 3-D edge points are mapped to 2-D plane with the help of perspective transformation. A novel algorithm has been proposed for the establishment of automatic correspondence between the corner points in both the edge maps. The method for automatic fusion of edge maps using affine transformation followed by iterative closest point algorithm has been introduced. Range and intensity images are complementary in nature and provide a richness of description which is not possible with either source in isolation.","PeriodicalId":349149,"journal":{"name":"2009 IEEE Symposium on Computational Intelligence for Image Processing","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134363529","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

Adaptive λ-enhancement: Type I versus type II fuzzy implementation 自适应λ增强:I型与II型模糊实现

2009 IEEE Symposium on Computational Intelligence for Image Processing Pub Date : 2009-05-15 DOI: 10.1109/CIIP.2009.4937872

H. Tizhoosh

引用次数: 3