Scale-Space from a Level Lines Tree
SCALE-SPACE '99 Proceedings of the Second International Conference on Scale-Space Theories in Computer Vision
A Variational Model for P+XS Image Fusion
International Journal of Computer Vision
Level Lines Selection with Variational Models for Segmentation and Encoding
Journal of Mathematical Imaging and Vision
Shape-based Invariant Texture Indexing
International Journal of Computer Vision
Mixed color/level lines and their stereo- matching with a modified Hausdorff distance
Integrated Computer-Aided Engineering
SIAM Journal on Imaging Sciences
Shape recognition via an a contrario model for size functions
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part II
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We propose a method for image registration which seems to be useful under the three following conditions. First, both images are globally and roughly the result of a translation and rotation. Second, some occlusions due to moving objects occur from image 1 to image 2. Third, because of changes of illumination, contrast may have changed globally and even locally. Under such unfavorable conditions, correlation-based global registration may become inaccurate, because of the global compromise it yields between several displacements. Our method avoids these difficulties by defining a set of local contrast invariant features in order to achieve contrast invariant matching. A voting procedure allows one to eliminate "wrong" matching features due to the displacement of small objects and yields sub-pixel accuracy. This method was tested successfully for registration of watches with moving hands and for road control applications.