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International Work Conference on Bio-inspired Intelligence (IWOBI)

作者： S. Calderón A. Sáenz R. Mora F. Siles I. Orozco M.E. Buemi Department of Electrical Engineering School of Engineering Cancer-Lab Universidad de Costa Rica San José Costa Rica Image Processing and Computer Vision Group Universidad de Buenos Aires Buenos Aires Argentina

This paper presents a new image abstraction approach, aiming to improve typical image related pattern recognition tasks such as segmentation, tracking, and classification. The proposed image abstraction framework performs image denoising and homogeneous region simplification, along with border and region enhancement. The proposed framework consists in a novel generalized approach of common weighted averaging denoising algorithms mixed with Unsharp Masking (USM) border enhancement techniques, to avoid typical USM artifacts as ringing. Results of the different configurations within the image abstraction framework for a cell tracking application are presented.

关键词： image edge detection Noise reduction Histograms AWGN Pattern recognition image segmentation

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Development of young oil palm tree recognition using Haar- based rectangular windows

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IOP Conference Series: Earth and Environmental Science 2016年第1期37卷

作者： S Daliman S A R Abu-Bakar S H Md Nor Azam Computer Vision Video and Image Processing (CvviP) Research Lab Department of Electronics and Computer Engineering Faculty of Electrical Engineering Universiti Teknologi Malaysia 81310 Skudai Johor MALAYSIA. Sime Darby Research Sdn. Bhd. Jalan Pulau Carey 42960 Pulau Carey Selangor MALAYSIA.

This paper presents development of Haar-based rectangular windows for recognition of young oil palm tree based on WorldView-2 imagery data. Haar-based rectangular windows or also known as Haar-like rectangular features have been popular in face recognition as used in Viola-Jones object detection framework. Similar to face recognition, the oil palm tree recognition would also need a suitable Haar-based rectangular windows that best suit to the characteristics of oil palm tree. A set of seven Haar-based rectangular windows have been designed to better match specifically the young oil palm tree as the crown size is much smaller compared to the matured ones. Determination of features for oil palm tree is an essential task to ensure a high successful rate of correct oil palm tree detection. Furthermore, features that reflects the identification of oil palm tree indicate distinctiveness between an oil palm tree and other objects in the image such as buildings, roads and drainage. These features will be trained using support vector machine (SVM) to model the oil palm tree for classifying the testing set and subimages of WorldView-2 imagery data. The resulting classification of young oil palm tree with sensitivity of 98.58% and accuracy of 92.73% shows a promising result that it can be used for intention of developing automatic young oil palm tree counting.

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Algorithm to extract the shortest linear edge and the longest diagonal of single isolated human insulin crystals for in-situ microscopy

Algorithm to extract the shortest linear edge and the longes...

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International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)

作者： G. Martinez P. Lindner A. Bluma T. Scheper Image Processing and Computer Vision Escuela de Ingeniería Eléctrica Universidad San José Costa Rica Institut für Technische Chemie (TCI) Leibniz Universität Hannover Callinstrasse 5 30167 Hannover Germany

In this contribution, an algorithm is presented, which is able to extract the shortest linear edge and the longest diagonal of each single isolated human insulin crystal region, which is found in an arbitrary image captured by an insitu microscope inside of a reactor, where a human insulin crystallization processes is taking place. First, the image regions of the single isolated crystals are segmented by combining three different techniques: thresholding, single nearest prototype classification and snakes. Then, the image positions of the vertices of each single isolated crystal region are determined by using the Hough Transformation. Finally, both the shortest linear edge and the longest diagonal of each single isolated crystal region are extracted by measuring and comparing distances between the found image positions of the single isolated crystal region vertices. Experimental results revealed an absolute length error of 4.18 percent and 2.32 percent of the extracted shortest linear edges and the extracted longest diagonals, respectively.

关键词： image segmentation Insulin image edge detection Microscopy Prototypes Crystallization

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An approach to large scale interactive retrieval of cultural heritage

An approach to large scale interactive retrieval of cultural...

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2014 Eurographics Workshop on Graphics and Cultural Heritage, GCH 2014

作者： Takami, Masato Bell, Peter Ommer, Bjrn Heidelberg Collaboratory for Image Processing IWR University of Heidelberg Germany Robert Bosch GmbH Corporate Research Computer Vision Research Lab Hildesheim Germany

ISBN: (纸本)9783905674637

Large scale digitization campaigns are simplifying the accessibility of a rapidly increasing number of images from cultural heritage. However, digitization alone is not sufficient to effectively open up these valuable resources. Retrieval and analysis within these datasets is currently mainly based on manual annotation and laborious preprocessing. This is not only a tedious task, which rapidly becomes infeasible due to the enormous data load. We also risk to be biased to only see what an annotator beforehand has focused on. Thus a lot of potential is being wasted. One of the most prevalent tasks is that of discovering similar objects in a dataset to find relations therein. The majority of existing systems for this task are detecting similar objects using visual feature keypoints. While having a low processing time, these methods are limited to detect only close duplicates due to their keypoint based representation. In this work we propose a search method which can detect similar objects even if they exhibit considerable variability. Our procedure learns models of the appearance of objects and trains a classifier to find related *** address a central problem of such learning-based methods, the need for appropriate negative and positive training samples. To avoid a highly complicated hard negative mining stage we propose a pooling procedure for gathering generic negatives. Moreover, a bootstrap approach is presented to aggregate positive training samples. Comparison of existing search methods in cultural heritage benchmark problems demonstrates that our approach yields significantly improved detection performance. Moreover, we show examples of searching across different types of datasets, e.g., drafts and photographs. © 2014 All rights reserved.

关键词： Benchmarking

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2D-PCA shape models: Application to 3D reconstruction of the human teeth from a single image

2D-PCA shape models: Application to 3D reconstruction of the...

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3rd International MICCAI Workshop on Medical computer vision, MCV 2013

作者： Abdelrehim, Aly S. Farag, Aly A. Shalaby, Ahmed M. El-Melegy, Moumen T. Computer Vision and Image Processing Laboratory University of Louisville Louisville KY 40292 United States Electrical Engineering Department Assiut University Assiut 71516 Egypt

ISBN: (纸本)9783319055299

Accurate modeling of human teeth is mandatory for many reasons. Some of them are (1) Providing comfort to patients during mold process, and (2) Enhancing the accuracy level for oral orthodontist and dental care personnel. Shape from Shading (SFS) proved to be of great help in this problem, considering the fact that human tooth surface is textureless. In this paper, we address the problem of 3D tooth reconstruction, and improve the current algorithms. The approached developed in this paper reconstructs the teeth from single image shading with 2D-PCA shape priors that have more sophisticated reflectance model. Oren-Nayar-Wolff model was used for modeling the surface reflectance. This formulation uses shape priors as got from a set of training CT scans of real human teeth. Our experiments show promising quantitative results, which builds the infrastructure for having an optical based approach that accounts for inexpensive and radiationless human tooth reconstruction. © 2014 Springer International Publishing Switzerland.

关键词： computerized tomography

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Human object classification in daubechies complex wavelet domain 2nd

Human object classification in daubechies complex wavelet do...

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2nd International Conference on Context-Aware Systems and Applications, ICCASA 2013

作者： Khare, Manish Srivastava, Rajneesh Kumar Khare, Ashish Binh, Nguyen Thanh Dien, Tran Anh Image Processing and Computer Vision Lab Department of Electronics and Communication University of Allahabad Allahabad India Ho Chi Minh City University of Technology Ho Chi Minh Viet Nam

ISBN: (纸本)9783319059389

Human object classification is an important problem for smart video surveillance applications. In this paper we have proposed a method for human object classification, which classify the objects into two classes: human and non-human. The proposed method uses Daubechies complex wavelet transform coefficients as a feature of object. Daubechies complex wavelet transform is used due to its better edge representation and approximate shift-invariant property as compared to real valued wavelet transform. We have used Adaboost as a classifier for classification of objects. The proposed method has been tested on standard datasets like, INRIA dataset. Quantitative experimental evaluation results show that the proposed method is better than other state-of-the-art methods and gives better performance. © Springer International Publishing Switzerland 2014.

关键词： Adaptive boosting

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One-sided transparency: A novel visualization for tubular objects

One-sided transparency: A novel visualization for tubular ob...

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作者： Curtin, Robert Ismail, Marwa Farag, Aly Sites, Chuck Elshazly, Salwa Falk, Robert Computer Vision and Image Processing Laboratory University of Louisville LouisvilleKY United States Kentucky Imaging Technologies LouisvilleKY United States Medical Imaging Jewish Hospital Abraham Flexner Way Louisville United States

ISBN: (纸本)9781479957514

This paper describes a unique method for tubular object visualization. The method involves rendering the exterior of the tube invisible while keeping the interior visible. This 'One-sided-transparency' technique renders a more complete view of the tube's interior. When applied to virtual colonoscopy (VC), it compares favorably to existing methods. It provides more complete images, reduces computational time, and reduces memory requirements while preserving VCs benefits for patients and practitioners. The approach also has various potential uses outside of VC. © 2014 IEEE.

关键词： Transparency

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ONE-SIDED TRANSPARENCY: A NOVEL VISUALIZATION FOR TUBULAR OBJECTS

ONE-SIDED TRANSPARENCY: A NOVEL VISUALIZATION FOR TUBULAR OB...

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IEEE International Conference on image processing

作者： Robert Curtin Marwa Ismail Aly Farag Chuck Sites Salwa Elshazly Robert Falk Computer Vision and Image Processing Laboratory University of Louisville Kentucky Imaging Technologies Medical Imaging Jewish Hospital

ISBN: (纸本)9781479957521

This paper describes a unique method for tubular object visualization. The method involves rendering the exterior of the tube invisible while keeping the interior visible. This "One-sided-transparency" technique renders a more complete view of the tube's interior. When applied to virtual colonoscopy (VC), it compares favorably to existing methods. It provides more complete images, reduces computational time, and reduces memory requirements while preserving VCs benefits for patients and practitioners. The approach also has various potential uses outside of VC.

关键词： Virtual colonoscopy Colorectal cancer Screening Fly-over One-sided transparency Centerlines

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STATISTICAL MORPHABLE MODEL FOR HUMAN TEETH RESTORATION

STATISTICAL MORPHABLE MODEL FOR HUMAN TEETH RESTORATION

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IEEE International Conference on image processing

作者： Eslam Mostafa Shireen Elhabian Aly Abdelrahim Salwa Elshazly Aly Farag Computer Vision and Image Processing Laboratory University of Louisville KY USA Kentucky Imaging Technologies Louisville KY USA

While traditional dental fillings are molded during a dental visit, dental restoration (e.g. inlays and onlays) are fabricated in a dental lab to offer a long lasting reparative solution to tooth decay or similar structural damage. Such process requires dental technicians who are highly trained experts in tooth anatomy to pick an appropriate standard tooth model from a tooth database. The success of a restoration process primarily relies on the acquisition and modeling of an accurate 3D shape of the occlusal surface of interest for manufacturing purposes. Based on a single optical image, this paper provides an economical and automated solution for tooth restoration where user intervention is kept at the minimal. The inherit relation between the photometric information and the underlying 3D shape is formulated as a coupled statistical model where the effect of illumination is modeled using Spherical Harmonics. Moreover, shape and texture alignment is accomplished using a proposed definition of anatomical jaw landmarks which are automatically detected. The system is evaluated on database of 32 jaws for crown, inlay, and onlay restoration. Results shows a promising performance for using the proposed approach in clinical application.

关键词： Teeth Shape Solid modeling Three-dimensional displays image restoration Dentistry Lighting

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Maximum likelihood thresholding algorithm based on four-parameter gamma distributions

Maximum likelihood thresholding algorithm based on four-para...

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International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)

作者： Peter De-Ford Geovanni Martinez Image Processing and Computer Vision Research Laboratory (IPCV-LAB) Universidad de Costa Rica San José Costa Rica

In this contribution, we present a segmentation algorithm based on thresholding to subdivide an intensity image in the regions of object and background. The optimal threshold is found by maximizing a likelihood function derived from a novel intensity probability density function model, which consists of the sum of two weighted four-parameter gamma distributions, as a more flexible alternative to currently used models consisting of the sum of two weighted two-parameter Gaussian distributions. According to our experiments with 132 images, the proposed algorithm is in average slightly better than the best found in the scientific literature, performing particularly good in low contrast images. The additional parameters and complexity of its likelihood function resulted in an increase of the processing time by a factor of 3, from 0.003 sec/image to 0.009 sec/image.

关键词： image segmentation Probability density function Approximation algorithms Gaussian distribution Histograms Shape Pattern recognition

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