Leyza Baldo Dorini

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Cell segmentation is a challenging problem due to both the complex nature of the cells and the uncertainty present in video microscopy. Manual methods for this purpose are onerous, imprecise and highly subjective, thus requiring automated methods that perform this task in an objective and efficient way. In this paper, we propose a novel method to segment(More)
This paper approaches novel methods to segment the nucleus and cytoplasm of white blood cells (WBC). This information is the basis to perform higher level tasks such as automatic differential counting, which plays an important role in the diagnosis of different diseases. We explore the image simplification and contour regularization resulting from the(More)
Accurate feature tracking is the foundation of many high level tasks in computer vision, such as 3D reconstruction and motion analysis. Although there are many feature tracking algorithms, most of them do not maintain information about the error of the data being tracked. Also, due to the difficulty and spatial locality of the problem, existing methods can(More)
Accurate feature tracking is the foundation of several high level tasks, such as 3D reconstruction and motion analysis. Although there are many feature tracking algorithms, most of them do not maintain information about the error of the data being tracked. In this paper, we propose a new generic framework that uses the scaled unscented transform (SUT) to(More)
Scale dependent signal representations have proved to be useful in several image processing applications. In this paper, we define a toggle operator for binarization/segmentation purposes based on scaled versions of an image transformed by morphological operations. The toggle decision rule, determining the new value of a pixel, considers local spatial(More)
Face recognition is being intensively studied in the areas of computer vision and pattern recognition. Working on still images with multiple faces is a challenging task due to the inherent characteristics of the images, the presence of blur, noise and occlusion, as well as variations of illumination, pose, rotation and scale. Besides being invariant to(More)
Face identification and verification are parts of a face recognition process. The verification of faces involves the comparison of an input face to a known face to verify the claim of identity of an individual. Hence, the verification process must determine the similarity between two face images , a face object image and a target face image. In order to(More)