Abstract Inaccurate localization of wildfire boundary will adversely affect the efficiency fire fighting, especially in case limited water for aerial dumping. This paper formulates detection occluded as a shape completion problem and introduces new solution. Different from traditional algorithms which only consider contour geometry, proposed algorithm takes partially visible surface geometry in...

In this paper, we address the boundary detection task motivated by the ambiguities in current definition of edge detection. To this end, we generate a large database consisting of more than 10k images (which is 20× bigger than existing edge detection databases) along with ground truth boundaries between 459 semantic classes including both foreground objects and different types of background, an...

The detection of the pectoral muscle boundary in the medio-lateral oblique view of mammograms is essential to improving the computer-aided diagnosis of breast cancer. In this study, a shape-based detection method is proposed for accurately extracting the boundary of the pectoral muscle in mammograms. A shape-based enhancement mask is applied to the mammogram and the initial boundary is then def...

State-of-the-art learning based boundary detection methods require extensive training data. Since labelling object boundaries is one of the most expensive types of annotations, there is a need to relax the requirement to carefully annotate images to make both the training more affordable and to extend the amount of training data. In this paper we focus on learning object boundaries in a weakly ...

In this paper, we describe a solution method for sentence boundary detection in Turkish. The method exploits simple heuristic knowledge of Turkish syllabication and its phonetic rules for disambiguation of dots. The test accuracy of the algorithm is measured as 96.02%. The main contribution of this study is considered as presenting a new lexicon free method for differentiating EOS (end of sente...

In this paper, we present a robust and accurate method for the segmentation of cross-sectional boundaries of vessels found in contrast-enhanced (CE) CTA and MRA images. The proposed algorithm first detects the edges along 1D rays in multiple scales by using mean-shift analysis. Second, edges from different scales are accurately and efficiently combined by using the properties of mean-shift clus...

We use a statistical framework for finding boundaries and for partitioning scenes into homogeneous regions. The model is a joint probability distribution for the a r ray of pixel gray levels and an a r ray of “labels.” In boundary finding, the labels a re binary, zero, or one, representing the absence o r presence of boundary elements. In partitioning, the label values a r e generic: two labels...

This paper describes the application of Bayesian networks to the generation of explanations for the evidence provided by one or more 1-D profiles. Experiments with synthetic images and Cephalograms are described.