| Records |
| Author |
Ernest Valveny; Enric Marti |
| Title |
A model for image generation and symbol recognition through the deformation of lineal shapes |
Type |
Journal Article |
| Year |
2003 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
| Volume |
24 |
Issue |
15 |
Pages |
2857-2867 |
| Keywords |
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| Abstract |
We describe a general framework for the recognition of distorted images of lineal shapes, which relies on three items: a model to represent lineal shapes and their deformations, a model for the generation of distorted binary images and the combination of both models in a common probabilistic framework, where the generation of deformations is related to an internal energy, and the generation of binary images to an external energy. Then, recognition consists in the minimization of a global energy function, performed by using the EM algorithm. This general framework has been applied to the recognition of hand-drawn lineal symbols in graphic documents. |
| Address |
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Thesis |
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| Publisher |
Elsevier Science Inc. |
Place of Publication |
New York, NY, USA |
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Edition |
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| ISSN |
0167-8655 |
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| Notes |
DAG; IAM |
Approved |
no |
| Call Number |
IAM @ iam @ VAM2003 |
Serial |
1653 |
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| Author |
Fernando Vilariño; Petia Radeva |
| Title |
Cardiac Segmentation with Discriminant Active Contours |
Type |
Book Chapter |
| Year |
2003 |
Publication |
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Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
211–217 |
| Keywords |
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| Abstract |
Dynamic tracking of heart moving is one relevant target in medical imag- ing and can be helpful for analyzing heart dynamics in the study of several cardiac diseases. For this aim, a previous segmentation problem of such structures is stated, based on certain relevant features (like edges or intensity levels, textures, etc.) Clas- sical active models have been used, but they fail when overlapping structures or not well-defined contours are present. Automatic feature learning systems may be a pow- erful tool. Discriminant active contours present optimal results in this kind of problem. They are a kind of deformable models that converge to an optimal object segmenta- tion that dynamically adapts to the object contour. The feature space is designed from a filter bank in order to guarantee the search and learning of the set of relevant fea- tures for optimal classification on each part of the object. Tracking of target evolution is obtained through the whole set of images, using information from the actual and previous stages. Feedback systems are implemented to guarantee the minimum well- separable classification set in each segmentation step. Our implementation has been proved with several series of Magnetic Resonance with improved results in segmenta- tion in comparison to previous methods. |
| Address |
Palma de Mallorca |
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Thesis |
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| Publisher |
IOS Press |
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Conference |
CCIA |
| Notes |
MV;MILAB;SIAI |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ ViR2003; IAM @ iam @ VRa2003 |
Serial |
426 |
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| Author |
Oriol Rodriguez-Leor; J. Mauri; Eduard Fernandez-Nofrerias; C. Garcia; R. Villuendas; Vicente del Valle; Debora Gil; Petia Radeva |
| Title |
Reconstruction of a spatio-temporal model of the intima layer from intravascular ultrasound sequences |
Type |
Journal Article |
| Year |
2003 |
Publication |
European Heart Journal |
Abbreviated Journal |
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Issue |
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Pages |
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Conference |
ESC Congress |
| Notes |
IAM;MILAB |
Approved |
no |
| Call Number |
IAM @ iam @ RMF2003c |
Serial |
1641 |
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| Author |
Josep Llados; Ernest Valveny; Gemma Sanchez; Enric Marti |
| Title |
A Case Study of Pattern Recognition: Symbol Recognition in Graphic Documentsa |
Type |
Conference Article |
| Year |
2003 |
Publication |
Proceedings of Pattern Recognition in Information Systems |
Abbreviated Journal |
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Issue |
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Pages |
1-13 |
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| Abstract |
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| Address |
Angers, France |
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Thesis |
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| Publisher |
ICEIS Press |
Place of Publication |
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ISBN |
972-98816-3-4 |
Medium |
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Expedition |
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Conference |
PRIS'03 |
| Notes |
DAG;IAM; |
Approved |
no |
| Call Number |
IAM @ iam @ LVS2003 |
Serial |
1576 |
| Permanent link to this record |
