The objective of semantic segmentation in microscopic images is to extract the cellular, nuclear or tissue components. This problem is challenging due to the large variations of features of these components (size, shape, orientation or texture). In this paper we present an automatic technique to robustly delimit the epithelial area (crypts) in microscopic images taken from colon tissues section...

We introduce the concept of edge-based component-trees for images with an arbitrary number of channels. The approach is a natural extension of the classical component-tree devoted to gray-scale images. The similar structure enables the translation of many gray-level image processing techniques based on the componenttree to hyperspectral and color images. As an example application, we present an...

Maximally stable extremal regions MSER is a state-of-the-art method in local feature detection. However, this method is sensitive to blurring because, in blurred images, the intensity values in region boundary will vary more slowly, and this will undermine the stability criterion that the MSER relies on. In this paper, we propose a method to improve MSER, making it more robust to image blurring...

Keywords: mathematical morphology segmentation connected component attribute profile elongation area stability multiphoton microscopy In this paper, a method to segment elongated objects is proposed. It is based on attribute profiles and area stability. Images are represented as component trees using a threshold decomposition. Then, some attributes are computed on each node of the tree. Finally...

Accurate image correspondence is crucial for estimating multiple-view geometry. In this paper, we present a registration-based method for improving accuracy of the image correspondences. We apply the method to fundamental matrix estimation under practical situations where there are both erroneous matches (outliers) and small feature location errors. Our registration-based method can correct fea...

A system is proposed for the recognition of the number of the dots on dice in general table game settings. Different from previous dice recognition systems which use a single top-view camera and work only under controlled illumination, the proposed one uses multiple cameras and works for uncontrolled illumination. Under controlled illumination edges are the prominent features considered by most...

This paper describes the signature as a one of the most robust and widely used trait in biometric verification. The signature is also known as behavioral biometric property. We present comparative analysis of offline signature recognition based on Dynamic Time Warping (DTW) and Maximally Stable Extremely Regions (MSER). The MSER system reported accuracy of 95. 371% where FAR is 5. 25% and FRR i...

We describe the prototype of an image retrieval system used for mobile guide applications. It allows users to send image queries of urban scenes using camera phones. The system uses a database of views of scenes to determine the poses of query views provided by the users. Information are then mapped onto the query views. Our approach is based on a fully affine invariant descriptor, coined PRIUS...

This thesis presents a robust online learning and recognition system. The basic idea is to exploit information from tracking an object during the recognition and/or learning stage to obtain increased robustness and better recognition results. Object tracking by means of an extended MSER tracker is utilized to extract local features and construct their trajectories. Compact object representation...

A general method for text localization and recognition in real-world images is presented. The proposed method is novel, as it (i) departs from a strict feed-forward pipeline and replaces it by a hypothesesverification framework simultaneously processing multiple text line hypotheses, (ii) uses synthetic fonts to train the algorithm eliminating the need for time-consuming acquisition and labelin...