2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA)最新文献_第2页

Anomaly Detection of Man-Made Objects in Large Aerial Images 航空大图像中人造物体的异常检测

2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2015-11-01 DOI: 10.1109/DICTA.2015.7371232

C. Pontecorvo, J. Sherrah

引用次数: 0

DIC Microscopy Image Reconstruction Using a Novel Variational Framework 用一种新的变分框架重建DIC显微图像

2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2015-11-01 DOI: 10.1109/DICTA.2015.7371252

K. Koos, József Molnár, P. Horváth

{"title":"DIC Microscopy Image Reconstruction Using a Novel Variational Framework","authors":"K. Koos, József Molnár, P. Horváth","doi":"10.1109/DICTA.2015.7371252","DOIUrl":"https://doi.org/10.1109/DICTA.2015.7371252","url":null,"abstract":"Quantitative microscopy (QM) became a key tool in systems-level drug discovery and disease diagnosis such as cancers and neurodegenerative disorders. However, to date QM is limited to epifluorescence microscopy which requires chemical labels, special imaging modality and often causes phototoxicity. Differential Interference Contrast (DIC) microscopy is label free and is low-phototoxic, thus it has great advantages over epifluorescence microscopy in numerous applications. Yet, DIC is not used for QM because the acquired images are not feasible directly for quantitative analysis. In this paper we propose a novel variational framework for DIC image reconstruction, enabling the modality for QM. Our energy functional uses a term that ensures similarity to the original DIC image and the total variation regularization term. The first term utilizes the point spread function (PSF) of the DIC microscope. The PSF is incorporated to our model by local integrals. We show that the derivation operation can be moved from the kernel to the image, which significantly accelerates the computations. The method outperforms other algorithms on synthetic and real DIC images.","PeriodicalId":214897,"journal":{"name":"2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130898955","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

Building Change Detection Based on Markov Random Field: Exploiting Both Pixel and Corner Features 基于马尔可夫随机场的建筑变化检测:利用像素和角点特征

2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2015-11-01 DOI: 10.1109/DICTA.2015.7371244

Kaibin Zong, A. Sowmya, J. Trinder

{"title":"Building Change Detection Based on Markov Random Field: Exploiting Both Pixel and Corner Features","authors":"Kaibin Zong, A. Sowmya, J. Trinder","doi":"10.1109/DICTA.2015.7371244","DOIUrl":"https://doi.org/10.1109/DICTA.2015.7371244","url":null,"abstract":"Map databases usually suffer from obsolete scene details due to frequently occurring changes, therefore automatic change detection has become vital. Previous research has demonstrated that Markov random field (MRF) is an effective method for image classification, in which both per pixel features and contextual relations between neighbouring points are incorporated into one framework, and the problem solved by means of maximum a posteriori (MAP) criterion. However, with the advent of high resolution images, other types of spatial information (e.g. corners and edges) can also be extracted and treated as clues for detecting changes, which is usually ignored in the previous work. In this paper, we propose a framework for building change detection from high resolution images based on Markov random field that exploits all spectral, spatial and contextual features. The initial detection results are obtained based on pixel level classification and MRF. Following that, corners are extracted and building corner candidates are determined via classification. All candidates are then refined based on previous MRF results and connected by a weighted edge map. Hereafter, building changes are initialized by the area included in the connected corners (refined) and the MRF is optimized again to improve previous outputs. Final results are achieved after some suitable post processing steps. Experimental results demonstrate the capability of the proposed method for building change detection and the usefulness of spatial features.","PeriodicalId":214897,"journal":{"name":"2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131734045","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

Evaluation Protocol of Skeletonization Applied to Grayscale Curvilinear Structures 应用于灰度曲线结构的骨架化评价方案

2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2015-11-01 DOI: 10.1109/DICTA.2015.7371256

Rabaa Youssef, A. Ricordeau, S. Sevestre, A. Benazza-Benyahia

{"title":"Evaluation Protocol of Skeletonization Applied to Grayscale Curvilinear Structures","authors":"Rabaa Youssef, A. Ricordeau, S. Sevestre, A. Benazza-Benyahia","doi":"10.1109/DICTA.2015.7371256","DOIUrl":"https://doi.org/10.1109/DICTA.2015.7371256","url":null,"abstract":"Few evaluation protocols were suggested to assess quality of skeletonization methods of grayscale images. Most of these protocols employ criteria and images both devoted to target application. No common image databases are available and the validation of skeleton structural properties under grayscale object variability suffers from a lack of standardized procedures. These properties are namely the preservation of geometry, topology and extremities respectively related to skeleton location and morphological quality. In this paper, we propose an evaluation protocol for skeletonization applied to grayscale curvilinear structures that focuses on skeleton structural properties, regardless of application specificities. We first identify challenging situations for skeletonizing grayscale images an then, construct a synthetic image database of objects with varying contrast, curvature and width. Secondly, we focus on criteria that reflect skeleton structural properties to assess its quality and noise robustness. We apply the proposed protocol on skeletonization methods within differential geometry framework that highlights good skeleton location and morphological thinning category that promotes skeleton connectivity. Experimental results indicate that the proposed protocol is able to describe the behavior of the criteria regarding the structural rendering of skeletonization methods.","PeriodicalId":214897,"journal":{"name":"2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123379431","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

Rotation Invariant Spatial Pyramid Matching for Image Classification 旋转不变空间金字塔匹配图像分类

2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2015-11-01 DOI: 10.1109/DICTA.2015.7371303

Priyabrata Karmakar, S. Teng, Guojun Lu, Dengsheng Zhang

引用次数: 9

Improved Impulse Noise Removal with Generalized Median Filter 改进的广义中值滤波脉冲噪声去除方法

2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2015-11-01 DOI: 10.1109/DICTA.2015.7371272

Duc-Son Pham

引用次数: 1

Creating Simplified 3D Models with High Quality Textures 使用高质量纹理创建简化的3D模型

2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2015-11-01 DOI: 10.1109/DICTA.2015.7371249

Song Liu, W. Li, P. Ogunbona, Yang-Wai Chow

引用次数: 5

Fast and Robust Edge Extraction in Unorganized Point Clouds 无组织点云快速鲁棒边缘提取

2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2015-11-01 DOI: 10.1109/DICTA.2015.7371262

Dena Bazazian, J. Casas, Javier Ruiz-Hidalgo

{"title":"Fast and Robust Edge Extraction in Unorganized Point Clouds","authors":"Dena Bazazian, J. Casas, Javier Ruiz-Hidalgo","doi":"10.1109/DICTA.2015.7371262","DOIUrl":"https://doi.org/10.1109/DICTA.2015.7371262","url":null,"abstract":"Edges provide important visual information in scene surfaces. The need for fast and robust feature extraction from 3D data is nowadays fostered by the widespread availability of cheap commercial depth sensors and multi-camera setups. This article investigates the challenge of detecting edges in surfaces represented by unorganized point clouds. Generally, edge recognition requires the extraction of geometric features such as normal vectors and curvatures. Since the normals alone do not provide enough information about the geometry of the cloud, further analysis of extracted normals is needed for edge extraction, such as a clustering method. Edge extraction through these techniques consists of several steps with parameters which depend on the density and the scale of the point cloud. In this paper we propose a fast and precise method to detect sharp edge features by analysing the eigenvalues of the covariance matrix that are defined by each point's k-nearest neighbors. Moreover, we evaluate quantitatively, and qualitatively the proposed methods for sharp edge extraction using several dihedral angles and well known examples of unorganized point clouds. Furthermore, we demonstrate the robustness of our approach in the noisier real-world datasets.","PeriodicalId":214897,"journal":{"name":"2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125117828","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: 89

Anatomical Skin Segmentation in Reflectance Confocal Microscopy with Weak Labels 基于弱标记的反射共聚焦显微解剖皮肤分割

2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2015-11-01 DOI: 10.1109/DICTA.2015.7371231

Samuel Hames, M. Ardigó, H. Soyer, A. Bradley, T. Prow

{"title":"Anatomical Skin Segmentation in Reflectance Confocal Microscopy with Weak Labels","authors":"Samuel Hames, M. Ardigó, H. Soyer, A. Bradley, T. Prow","doi":"10.1109/DICTA.2015.7371231","DOIUrl":"https://doi.org/10.1109/DICTA.2015.7371231","url":null,"abstract":"Reflectance confocal microscopy (RCM) allows in-vivo microscopic examination of human skin and is emerging as a powerful tool for a wide range of dermatological problems. Clinical use of RCM is limited by the need for trained experts to interpret images and the lack of supporting tools for quantitative evaluation of the images, especially in large datasets. The first task in understanding RCM images is to understand and produce a segmentation of the anatomical strata of human skin. This work presents such an algorithm using only weak supervision, in the form of labels for whole en-face sections, to learn a per pixel segmentation of a complete RCM depth stack. Using a bag-of- features representation for image appearance, and a conditional random field model for strata labels through the depth of the skin, a structured support vector machine was trained to label individual pixels. The approach was developed and tested on a dataset of 308 depth stacks from 54 volunteers, consisting of 16,144 total en-face sections. This approach accurately classified 85.7% of sections in the test set, and was able to detect underlying changes in the skin strata thickness with age.","PeriodicalId":214897,"journal":{"name":"2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128033083","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: 13

Illumination Compensated Segmentation of Microscopic Images of Activated Sludge Flocs 活性污泥絮凝体显微图像的光照补偿分割

2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2015-11-01 DOI: 10.1109/DICTA.2015.7371265

Muhammad Burhan Khan, H. Nisar, C. Ng, P. K. Lo

{"title":"Illumination Compensated Segmentation of Microscopic Images of Activated Sludge Flocs","authors":"Muhammad Burhan Khan, H. Nisar, C. Ng, P. K. Lo","doi":"10.1109/DICTA.2015.7371265","DOIUrl":"https://doi.org/10.1109/DICTA.2015.7371265","url":null,"abstract":"Image processing and analysis is a useful tool for monitoring of activated sludge wastewater treatment plant. However its effectiveness is dependent on performance of the segmentation algorithms. The activated sludge plant is monitored by image processing and analysis of images acquired through trinocular microscope. The sample observed under microscope is collected from aeration tank of the plant. In this paper, a segmentation technique with integrated illumination compensation is proposed for the microscopic images of the activated sludge samples. The illumination noise was modeled and estimated as Gaussian distribution symmetric about a threshold value determined by global Otsu thresholding algorithm. The performance of the algorithm was evaluated using time required for segmentation, Rand index, accuracy and quantification of flocs. In order to compare with the state-of-the-art algorithms, gold approximations of ground truth images were manually prepared. The performance was assessed by combining the evaluation metrics in an integrated perspective. The proposed algorithm exhibits better performance in terms of both integrated and non-integrated perspectives.","PeriodicalId":214897,"journal":{"name":"2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","volume":"223 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113995292","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: 8