2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA)最新文献_第3页

Detection of Structural Similarity for Multimodal Microscopic Image Registration 多模态显微图像配准的结构相似性检测

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-12-23 DOI: 10.1109/DICTA.2013.6691495

Guohua Lv, S. Teng, Guojun Lu, M. Lackmann

引用次数: 3

Lq Averaging for Symmetric Positive-Definite Matrices 对称正定矩阵的Lq平均

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-12-23 DOI: 10.1109/DICTA.2013.6691505

Khurrum Aftab, R. Hartley

{"title":"Lq Averaging for Symmetric Positive-Definite Matrices","authors":"Khurrum Aftab, R. Hartley","doi":"10.1109/DICTA.2013.6691505","DOIUrl":"https://doi.org/10.1109/DICTA.2013.6691505","url":null,"abstract":"We propose a method to find the Lq mean of a set of symmetric positive-definite (SPD) matrices, for 1 ≤ q ≤ 2. Given a set of points, the Lq mean is defined as a point for which the sum of q-th power of distances to all the given points is minimum. The Lq mean, for some value of q, has an advantage of being more robust to outliers than the standard L2 mean. The proposed method uses a Weiszfeld inspired gradient descent approach to compute the update in the descent direction. Thus, the method is very simple to understand and easy to code because it does not required line search or other complex strategy to compute the update direction. We endow a Riemannian structure on the space of SPD matrices, in particular we are interested in the Riemannian structure induced by the Log-Euclidean metric. We give a proof of convergence of the proposed algorithm to the Lq mean, under the Log-Euclidean metric. Although no such proof exists for the affine invariant metric but our experimental results show that the proposed algorithm under the affine invariant metric converges to the Lq mean. Furthermore, our experimental results on synthetic data confirms the fact that the L1 mean is more robust to outliers than the standard L2 mean.","PeriodicalId":231632,"journal":{"name":"2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114383012","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

A Pedestrian Multiple Hypothesis Tracker Fusing Head and Body Detections 一种融合头部和身体检测的行人多假设跟踪器

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-12-23 DOI: 10.1109/DICTA.2013.6691474

J. Sherrah, B. Ristic, D. Kamenetsky

引用次数: 3

Biometric Security Application for Person Authentication Using Retinal Vessel Feature 利用视网膜血管特征进行身份认证的生物识别安全应用

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-12-23 DOI: 10.1109/DICTA.2013.6691489

Md. Akter Hussain, A. Bhuiyan, A. Mian, K. Ramamohanarao

{"title":"Biometric Security Application for Person Authentication Using Retinal Vessel Feature","authors":"Md. Akter Hussain, A. Bhuiyan, A. Mian, K. Ramamohanarao","doi":"10.1109/DICTA.2013.6691489","DOIUrl":"https://doi.org/10.1109/DICTA.2013.6691489","url":null,"abstract":"Retinal vascular branch and crossover points are unique features for each individual that can be used as a reliable biometric for personal authentication and can be used for information retrieval and security application. In this work, a novel biometric authentication scheme is proposed based on the retinal vascular network features. We apply an automatic technique to detect and identify retinal vascular branch and crossover points. These branch and crossover points are mapped from prominent blood vessels in the image. For this, a novel vessel width measurement method is applied and vessels more than certain widths are selected. Based on these vessel segments their corresponding branch and crossover points are identified. Invariant features are constructed through Geometric Hashing of the detected branch and crossover points. We consider the crossover points for modelling a basis pair and all other points together for locations in the hash table entries. Thus, the models are invariant to rotation, translation and scaling. For each person, the system is trained with the models to accept or reject a claimed identity. The initial results show that the proposed method has achieved 100% detection accuracy which is highly potential for reliable person identification.","PeriodicalId":231632,"journal":{"name":"2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126060390","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

Particle Detection and Classification in Photoelectric Smoke Detectors Using Image Histogram Features 基于图像直方图特征的光电烟雾探测器粒子检测与分类

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-12-23 DOI: 10.1109/DICTA.2013.6691509

K. Pahalawatta, R. Green

{"title":"Particle Detection and Classification in Photoelectric Smoke Detectors Using Image Histogram Features","authors":"K. Pahalawatta, R. Green","doi":"10.1109/DICTA.2013.6691509","DOIUrl":"https://doi.org/10.1109/DICTA.2013.6691509","url":null,"abstract":"Due to the failure of detecting smaller smoke particles (<; 1 nm in diameter) and the occurrence of false positives by commercially available photoelectric smoke detectors, a new detection algorithm was constructed by analyzing the image histogram features of smoke particles generated by Rayleigh scattered light to detect and classify the smoke particles of common household fires. Seven particle types were selected and exposed to a continuous spectrum of light in a closed particle chamber and a significant result was achieved over the common photoelectric smoke detectors by detecting all test particles using colour histograms. As Rayleigh theory suggested, comparing the intensities of scattered light of different wavelengths is the best method to classify different sized particles. Existing histogram comparison methods based on histogram bin values failed to evaluate a relationship between the scattered intensities of individual red, green and blue laser beams with different sized particles due to the uneven particles movements inside the chamber. The proposed classification algorithm which is based on a particle density independent feature, histogram maximum value index, classified all the monotype particles with 100% accuracy. As expected, the classifier failed to distinguish wood smoke from other monotype particles since wood smoke is itself a complex composition of many monotype particles.","PeriodicalId":231632,"journal":{"name":"2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126868777","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

Adaptive Morphological Filtering of Incomplete Data 不完全数据的自适应形态学滤波

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-12-23 DOI: 10.1109/DICTA.2013.6691479

A. Landström, M. Thurley, Håkan Jonsson

引用次数: 2

Kernel Partial Least Squares Based Hierarchical Building Change Detection Using High Resolution Aerial Images and Lidar Data 基于核偏最小二乘的高分辨率航空图像和激光雷达数据分层建筑变化检测

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-12-23 DOI: 10.1109/DICTA.2013.6691502

Kaibin Zong, A. Sowmya, J. Trinder

{"title":"Kernel Partial Least Squares Based Hierarchical Building Change Detection Using High Resolution Aerial Images and Lidar Data","authors":"Kaibin Zong, A. Sowmya, J. Trinder","doi":"10.1109/DICTA.2013.6691502","DOIUrl":"https://doi.org/10.1109/DICTA.2013.6691502","url":null,"abstract":"Map databases usually suffer from obsolete scene details due to frequently occurring changes, therefore automatic change detection has become vital. Recently, researchers have explored change detection by combining high resolution images with airborne lidar data to overcome the disadvantages of using images alone. However, multiple correlations between different features are usually ignored and false alarms will further depress the value of final detection result. In this paper, we propose an hierarchical framework for building change detection by fusing high resolution aerial images with airborne lidar data that provides elevation information. The kernel partial least squares (KPLS) method is introduced for dealing with feature correlations, and dimension reduction and pixel level change detection are conducted simultaneously in a single learning process. To address the relatively high false alarm rate, an object based post processing technique is proposed to further eliminate those pseudo candidates. All spectral, structural and contextual information are combined together in this step. Experimental results demonstrate the capability of our proposed method for building change detection.","PeriodicalId":231632,"journal":{"name":"2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129628206","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: 7

Taxonomy of File Fragments Using Gray-Level Co-Occurrence Matrices 基于灰度共生矩阵的文件片段分类

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-12-23 DOI: 10.1109/DICTA.2013.6691534

P. P. Pullaperuma, A. Dharmarathne

引用次数: 5

Undecoded Coefficients Recovery in Distributed Video Coding by Exploiting Spatio-Temporal Correlation: A Linear Programming Approach 利用时空相关性的分布式视频解码系数恢复:一种线性规划方法

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-12-23 DOI: 10.1109/DICTA.2013.6691535

Mortuza Ali, M. Murshed

{"title":"Undecoded Coefficients Recovery in Distributed Video Coding by Exploiting Spatio-Temporal Correlation: A Linear Programming Approach","authors":"Mortuza Ali, M. Murshed","doi":"10.1109/DICTA.2013.6691535","DOIUrl":"https://doi.org/10.1109/DICTA.2013.6691535","url":null,"abstract":"Distributed video coding (DVC) aims at achieving low-complexity encoding in contrast to the existing video coding standards' high complexity encoding. According to the Wyner-Ziv theorem this can be achieved, under certain conditions, by independent encoding of the frames while resorting to joint decoding. However, the performance of a Wyner-Ziv coding scheme significantly depends on its knowledge about the spatio-temporal correlation of the video. Unfortunately, correlation statistics in a video widely varies both along the spatial and temporal directions. Therefore, we argue that in a feedback free transform domain DVC scheme the decoder will fail to recover all the transform coefficients with a nonzero probability. Thus, we suggest to integrate a recovery method with the decoder that aims at recovering the undecoded coefficients by exploiting the spatio-temporal correlation of the video. Besides, we extend and modify a recovery scheme, recently proposed in the context of images, for DVC so that it exploits both spatial and temporal correlations in recovering the undecoded coefficients. The essential idea of this scheme is to formulate the recovery problem as a linear optimization problem which can be solved efficiently using linear programming. Our simulation results demonstrated that the proposed scheme can significantly improve the PSNR and visual quality of the erroneous video frames produced by a DVC decoder.","PeriodicalId":231632,"journal":{"name":"2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128856159","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

Biologically Significant Facial Landmarks: How Significant Are They for Gender Classification? 生物学上重要的面部标志:它们对性别分类有多重要?

2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2013-12-23 DOI: 10.1109/DICTA.2013.6691488

S. Z. Gilani, F. Shafait, A. Mian

引用次数: 24