Scale-Space Properties of the Multiscale Morphological Dilation-Erosion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Interpretation and Coding of Face Images Using Flexible Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Human Face Recognition with Different Statistical Features
Proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Illumination Normalized Face Image for Face Recognition
Proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Face Detection by Learned Affine Correspondences
Proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Face Detection Using Integral Projection Models
Proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
A Transformation-Based Mechanism for Face Recognition
Proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
A Robust Approach to Face and Eyes Detection from Images with Cluttered Background
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
Locating and extracting the eye in human face images
Pattern Recognition
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In this paper we resolve the problem of automatically normalize front view photos from a database that contain images of human faces with different size, angle and position. It was used a template with a standardized inter eye distance and dimensions. We are mapping all images to this template applying a geometrical transformation. It is necessary to obtain the eyes positions on image to calculate the transforms parameters. That is not a trivial problem. We use active contour to detect the human face. After that, we apply morphological filters to highlight image signal amplitude in the eyes positions. A set of criterion is applied to select a pair of point with more possibility to be the eyes. Then, a subroutine is feed with eyes coordinates to calculate and apply the geometrical transformation. Our method was applied to 500 photos and it performs very well in the 94% of all cases.