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Author |
Debora Gil; Petia Radeva |
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Title |
Inhibition of false landmarks |
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Journal Article |
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Year |
2006 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
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Volume |
27 |
Issue |
9 |
Pages |
1022-1030 |
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Abstract |
Corners and junctions are landmarks characterized by the lack of differentiability in the unit tangent to the image level curve. Detectors based on differential operators are not, by their own definition, the best posed as they require a higher degree of differentiability to yield a reliable response. We argue that a corner detector should be based on the degree of continuity of the tangent vector to the image level sets, work on the image domain and need no assumptions on neither the image local structure nor the particular geometry of the corner/junction. An operator measuring the degree of differentiability of the projection matrix on the image gradient fulfills the above requirements. Because using smoothing kernels leads to corner misplacement, we suggest an alternative fake response remover based on the receptive field inhibition of spurious details. The combination of both orientation discontinuity detection and noise inhibition produce our inhibition orientation energy (IOE) landmark locator. |
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Elsevier Science Inc. |
Place of Publication  |
New York, NY, USA |
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0167-8655 |
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Notes |
IAM;MILAB |
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no |
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Call Number |
IAM @ iam @ GiR2006 |
Serial |
1529 |
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Author |
Ernest Valveny; Enric Marti |
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Title |
A model for image generation and symbol recognition through the deformation of lineal shapes |
Type |
Journal Article |
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Year |
2003 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
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Volume |
24 |
Issue |
15 |
Pages |
2857-2867 |
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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. |
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Publisher |
Elsevier Science Inc. |
Place of Publication |
New York, NY, USA |
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0167-8655 |
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Notes |
DAG; IAM |
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no |
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Call Number |
IAM @ iam @ VAM2003 |
Serial |
1653 |
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Author |
Oriol Pujol; Debora Gil; Petia Radeva |
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Title |
Fundamentals of Stop and Go active models |
Type |
Journal Article |
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Year |
2005 |
Publication |
Image and Vision Computing |
Abbreviated Journal |
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Volume |
23 |
Issue |
8 |
Pages |
681-691 |
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Keywords |
Deformable models; Geodesic snakes; Region-based segmentation |
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Abstract |
An efficient snake formulation should conform to the idea of picking the smoothest curve among all the shapes approximating an object of interest. In current geodesic snakes, the regularizing curvature also affects the convergence stage, hindering the latter at concave regions. In the present work, we make use of characteristic functions to define a novel geodesic formulation that decouples regularity and convergence. This term decoupling endows the snake with higher adaptability to non-convex shapes. Convergence is ensured by splitting the definition of the external force into an attractive vector field and a repulsive one. In our paper, we propose to use likelihood maps as approximation of characteristic functions of object appearance. The better efficiency and accuracy of our decoupled scheme are illustrated in the particular case of feature space-based segmentation. |
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Butterworth-Heinemann |
Place of Publication |
Newton, MA, USA |
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0262-8856 |
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Notes |
IAM;MILAB;HuPBA |
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no |
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Call Number |
IAM @ iam @ PGR2005 |
Serial |
1629 |
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