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共 108 条记录，以下是61-70 订阅

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pattern recognition and image analysis 1

引用

丛书名： Lecture Notes in Computer Science

1000年

作者： Luís A. Alexandre José Salvador Sánchez João M. F. Rodrigues

ISBN: (数字)9783319588384

ISBN: (纸本)9783319588377

this book constitutes the refereed proceedings of the 8th iberian conference on pattern recognition and image analysis, ibpria 2017, held in Faro, Portugal, in June 2017. the 60 regular papers presented in this volume were carefully reviewed and selected from 86 submissions. they are organized in topical sections named: pattern recognition and Machine Learning; Computer Vision; image and Signal Processing; Medical image; and Applications.

关键词： pattern recognition Computer Graphics image Processing and Computer Vision Biometrics Artificial Intelligence

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Smoothed Disparity Maps for Continuous American Sign Language recognition

Smoothed Disparity Maps for Continuous American Sign Languag...

引用

4th iberian conference on pattern recognition and image analysis

作者： Dreuw, Philippe Steingrube, Pascal Deselaers, thomas Ney, Hermann Rhein Westfal TH Aachen Lehrstuhl Informat 6 Dept Comp Sci D-52056 Aachen Germany

ISBN: (纸本)9783642021718

For the recognition of continuous sign language we analyse whether we can improve the results by explicitly incorporating depth information. Accurate hand tracking for sign language recognition is made difficult by abrupt and fast changes in hand position and configuration, overlapping hands, or a hand signing in front of the face. In our system depth information is extracted using a stereo-vision method that considers the time axis by using pre- and succeeding frames. We demonstrate that depth information helps to disambiguate overlapping hands and thus to improve the tracking of the hands. However, the improved tracking has little influence on the final recognition results.

关键词： Stereo vision

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Segmentation of the Rectus Abdominis Muscle Anterior Fascia for the analysis of Deep Inferior Epigastric Perforators 8th

Segmentation of the Rectus Abdominis Muscle Anterior Fascia ...

引用

8th iberian conference on pattern recognition and image analysis (ibpria)

作者： Araujo, Ricardo J. Oliveira, Helder P. Univ Porto Fac Engn INESC TEC Porto Portugal

ISBN: (纸本)9783319588384;9783319588377

the segmentation of the anterior fascia of the rectus abdominis muscle is an important step towards the analysis of abdominal vasculature. It may advance Computer Aided Detection tools that support the activity of clinicians who study vessels for breast reconstruction using the Deep Inferior Epigastric Perforator flap. In this paper, we propose a two-fold methodology to detect the anterior fascia in Computerized Tomographic Angiography volumes. First, a slice-wise thresholding is applied and followed by a post-processing phase. Finally, an interpolation framework is used to obtain a final smooth fascia detection. We evaluated our method in 20 different volumes, by calculating the mean Euclidean distance to manual annotations, achieving subvoxel error.

关键词： Medical image Segmentation Abdominal anterior fascia

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Multi-modal Complete Breast Segmentation 8th

Multi-modal Complete Breast Segmentation

引用

8th iberian conference on pattern recognition and image analysis (ibpria)

作者： Zolfagharnasab, Hooshiar Monteiro, Joao P. Teixeira, Joao F. Borlinhas, Filipa Oliveira, Helder P. Univ Porto Fac Engn INESC TEC Porto Portugal EPE Portuguese Oncol Inst Lisbon IPOLFG Lisbon Portugal

ISBN: (纸本)9783319588384;9783319588377

Automatic segmentation of breast is an important step in the context of providing a planning tool for breast cancer conservative treatment, being important to segment completely the breast region in an objective way;however, current methodologies need user interaction or detect breast contour partially. In this paper, we propose a methodology to detect the complete breast contour, including the pectoral muscle, using multi-modality data. Exterior contour is obtained from 3D reconstructed data acquired from low-cost RGB-D sensors, and the interior contour (pectoral muscle) is obtained from Magnetic Resonance Imaging (MRI) data. Quantitative evaluation indicates that the proposed methodology performs an acceptable detection of breast contour, which is also confirmed by visual evaluation.

关键词： image analysis Bio-medical image processing Breast contour detection

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Sign Language Gesture recognition Using HMM 8th

Sign Language Gesture Recognition Using HMM

引用

8th iberian conference on pattern recognition and image analysis (ibpria)

作者： Parcheta, Zuzanna Martinez-Hinarejos, Carlos-D. Sciling SL Carrer Riu 321 Valencia 46012 Spain Univ Politecn Valencia Pattern Recognit & Human Language Technol Res Ctr Camino de Vera S-N E-46022 Valencia Spain

ISBN: (纸本)9783319588384;9783319588377

Gesture recognition is very useful in everyday life for tasks related to computer-human interaction. Gesture recognition systems are usually tested with a very large, complete, standardised and intuitive database of gesture: sign language. Unfortunately, such data is typically very large and contains very similar data which makes difficult to create a low cost system that can differentiate a large enough number of signs. this makes difficult to create a useful tool for allowing deaf people to communicate with the hearing people. the present work presents a sign recognition system for the Spanish sign language. the experiments conducted include separated gesture recognition and sequences of gestures. this work extends previous work by augmenting the size of data set (91 signs), higher than most of the state of the art systems (around 20 gestures). Apart from that, the proposed recognition system performs recognition of dynamic gestures, in contrast to most studies that use static gestures, which are easier to recognise. Finally, the work studies the recognition of sequences of gestures corresponding to grammatically correct phrases in Spanish sign language. For both tasks, Hidden Markov Models are used as recognition models. Results presented for classification of separated gestures are compared with other usual classification techniques, showing a better recognition performance. the current data set, which has been captured using the Leap Motion sensor, will be publicly available to the research community in gesture recognition.

关键词： Gesture classification Sign language translator HTK Leap Motion HMM K-NN DTW

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Automated Mammographic Risk Classification Based on Breast Density Estimation

Automated Mammographic Risk Classification Based on Breast D...

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6th iberian conference on pattern recognition and image analysis (ibpria)

作者： Chen, Zhili Oliver, Arnau Denton, Erika Zwiggelaar, Reyer Aberystwyth Univ Dept Comp Sci Aberystwyth SY23 3DB Dyfed Wales Univ Girona Dept Comp Architecture & Technol Girona 17071 Spain Norfolk & Norwich Univ Hosp Dept Radiol Norwich NR4 7UY Norfolk England

ISBN: (纸本)9783642386282

this paper presents a method for automated mammographic risk classification based on breast density estimation in mammograms. the overall profile of breast tissue density is represented using a topographic map, which is a hierarchical representation, obtained from the upper level sets of an image. A shape tree is constructed to describe the topological and geometrical structure of the shapes (i.e. connected components) within the topographic map. Two properties, saliency and independency, are defined to detect shapes of interest (i.e. dense regions) based on the shape tree. A density map is further generated focusing on dense regions, which provides a quantitative description of breast density. Finally, mammographic risk classification is performed based on the breast density measures derived from the density map. the validity of this method is evaluated using the full MIAS database and a large dataset taken from the DDSM database. A high agreement with expert radiologists is indicated according to the BIRADS density classification. the obtained classification accuracies are 76.01% and 81.22%, respectively.

关键词： Maps

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Automatic Documents Counterfeit Classification Using image Processing and analysis 8th

Automatic Documents Counterfeit Classification Using Image P...

引用

8th iberian conference on pattern recognition and image analysis (ibpria)

作者： Vieira, Rafael Antunes, Mario Silva, Catarina Assis, Ana Polytech Inst Leiria Sch Technol & Management Leiria Portugal Univ Coimbra CISUC Ctr Informat & Syst Dept Informat Engn Coimbra Portugal Univ Porto INESC TEC CRACS Porto Portugal Sci Police Lab Judiciary Police Lisbon Portugal

ISBN: (纸本)9783319588384;9783319588377

Counterfeit detection in official documents has challenged forensic experts on trying to correlate them to improve the identification of forgery authors by criminal investigators. Past counterfeit investigation on the Portuguese Police Forensic Laboratory allowed the construction of an organized set of digital images related to counterfeited documents, helping manual identification of new counterfeiters modus operandi. However, these images are usually stored in distinct resolutions, may have different sizes and could have been captured under different types of illumination. In this paper we present a methodology to automate a counterfeit identification modus operandi, by comparing a given document image with a database of previously catalogued counterfeited documents images. the proposed method ranks the identified counterfeited documents and allows the forensic experts to drive their attention to the most similar documents. It takes advantage of scalable algorithms under the OpenCV framework that compare images, match patterns and analyse textures and colours. We present a set of tests with distinct datasets with promising results.

关键词： image classification

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Is Kinect Depth Data Accurate for the Aesthetic Evaluation after Breast Cancer Surgeries?

Is Kinect Depth Data Accurate for the Aesthetic Evaluation a...

引用

6th iberian conference on pattern recognition and image analysis (ibpria)

作者： Oliveira, Helder P. Silva, Marco D. Magalhaes, Andre Cardoso, Maria J. Cardoso, Jaime S. Univ Porto INESC TEC Fac Engn Rua Campo Alegre 823 P-4100 Oporto Portugal Univ Porto Fac Med Porto Portugal Breast Univ Champalimaud Canc Ctr Champalimaud Fdn Porto Portugal

ISBN: (纸本)9783642386282

the conservative treatment is now the preferred procedure to treat breast cancer mainly due to better aesthetical results obtained. However, the aesthetic outcome is diverse and very difficult to evaluate, which motivates the research on automatic methodologies. the use of three-dimensional (3D) methodologies is increasing;however, the high cost of the equipment and the need for specialised technicians to operate it are import setbacks. Consequently, the search for affordable and easy to perform equipments is highly desirable. this paper studies the application of a Kinect device in this field, addressing issues related to accuracy, resolution and quality of the data. the paper demonstrates a comparative study of state-of-the-art Super-Resolution (SR) algorithms applied to the Kinect depth data, and the importance to improve the quality of images is stressed. the results demonstrate that it is possible to measure volumetric information and that there is agreement between features and the subjective aesthetic evaluation.

关键词： Biomedical image processing breast cancer conservative treatment aesthetic evaluation low-cost solutions

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Automated Detection and Categorization of Genital Injuries Using Digital Colposcopy 8th

Automated Detection and Categorization of Genital Injuries U...

引用

8th iberian conference on pattern recognition and image analysis (ibpria)

作者： Fernandes, Kelwin Cardoso, Jaime S. Astrup, Birgitte Schmidt INESC TEC Porto Portugal Univ Porto Porto Portugal Univ Southern Denmark Inst Forens Med Odense Denmark

ISBN: (纸本)9783319588384;9783319588377

Despite the existence of patterns able to discriminate between consensual and non-consensual intercourse, the relevance of genital lesions in the corroboration of a legal rape complaint is currently under debate in many countries. the testimony of the physicians when assessing these lesions has been questioned in court due to several factors (e.g. a lack of comprehensive knowledge of lesions, wide spectrum of background area, among others). thereby, it is relevant to provide automated tools to support the decision process in an objective manner. In this work, we compare traditional handcrafted features and deep learning techniques in the automated processing of colposcopic images for genital injury detection. Positive results where achieved by both paradigms in segmentation and classification subtasks, being traditional and deep models the best strategy for each subtask type respectively.

关键词： Genital injury Digital colposcopy Deep learning Handcrafted features image processing

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Chromatographic pattern recognition Using Optimized One-Class Classifiers

Chromatographic Pattern Recognition Using Optimized One-Clas...

引用

4th iberian conference on pattern recognition and image analysis

作者： Sousa, Antonio V. Mendonca, Ana Maria Campilho, Aurelio Inst Biomed Engn P-4200465 Oporto Portugal

ISBN: (纸本)9783642021718

this paper presents a method for automating the selection of the rejection rate of one-class classifiers aiming at optimizing the classifier performance. these classifiers are used in a new classification approach to deal with class imbalance in thin-Layer Chromatography (TLC) patterns, which is due to the huge difference between the number of normal and pathological cases, as a consequence of the rarity of Lysosomal Storage Disorders (LSD) diseases. the classification is performed in two decision stages, both implemented using optimized one-class classifiers: the first stage aims at recognizing most of the normal samples;the outliers of this first decision level are presented to the second stage, which is a multiclassifier prepared to deal with both pathological and normal patterns. the results that were obtained proved that the proposed methodology is able to overcome some of the difficulties associated with the choice of the rejection rate of one-class classifiers, and generally contribute to the minimization of the imbalance problem in TLC pattern classification.

关键词： thin layer chromatography

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