Topic
Distance transform
About: Distance transform is a research topic. Over the lifetime, 2886 publications have been published within this topic receiving 59481 citations.
Papers published on a yearly basis
Papers
More filters
02 Jul 2003
TL;DR: A new simple image-matching algorithm, robust image matching algorithm (RIMA), an extension to distance transform (chamfer) matching, which is time efficient, robust, rotation, scale and perspective invariant method.
Abstract: Image matching is an important task. There are many available methods for occluded image matching, e.g., Hausdorff distance and wavelet transform based matching. In this paper we propose new simple image-matching algorithm, robust image matching algorithm (RIMA), an extension to distance transform (chamfer) matching. Distance transform and conventional chamfer matching algorithm are explained. Different matching measures for RIMA are presented. Examples to demonstrate the algorithm and necessary results are also included. Proposed RIMA is time efficient, robust, rotation, scale and perspective invariant method.
28 citations
TL;DR: This study represented 3D structures by 2D maps of pairwise residue distances and developed a new method (SPROF) to predict protein sequence profile based on an image captioning learning frame, which is the first method to employ 2D distance map for predicting protein properties.
Abstract: Protein sequence profile prediction aims to generate multiple sequences from structural information to advance the protein design. Protein sequence profile can be computationally predicted by energy-based or fragment-based methods. By integrating these methods with neural networks, our previous method, SPIN2, has achieved a sequence recovery rate of 34%. However, SPIN2 employed only one-dimensional (1D) structural properties that are not sufficient to represent three-dimensional (3D) structures. In this study, we represented 3D structures by 2D maps of pairwise residue distances and developed a new method (SPROF) to predict protein sequence profiles based on an image captioning learning frame. To our best knowledge, this is the first method to employ a 2D distance map for predicting protein properties. SPROF achieved 39.8% in sequence recovery of residues on the independent test set, representing a 5.2% improvement over SPIN2. We also found the sequence recovery increased with the number of their neighbored residues in 3D structural space, indicating that our method can effectively learn long-range information from the 2D distance map. Thus, such network architecture using a 2D distance map is expected to be useful for other 3D structure-based applications, such as binding site prediction, protein function prediction, and protein interaction prediction. The online server and the source code is available at http://biomed.nscc-gz.cn and https://github.com/biomed-AI/SPROF, respectively.
28 citations
01 May 2020
TL;DR: A three-dimensional distance transform algorithm, which is a variant of 3D-DT, is applied to railway alignment optimization to solve the large-scale and time-consuming civil engineering problem of railroad alignment optimization.
Abstract: Railway alignment optimization is a large-scale and time-consuming civil engineering problem. To solve it, a three-dimensional distance transform (3D-DT) algorithm, which is a variant of th...
28 citations
24 Sep 2009
TL;DR: Two methods to generate a bird’s-eye image from the original input image are recalled and a modified version of the Euclidean distance transform called real orientation distance transform (RODT) is proposed.
Abstract: Lane detection and tracking is a significant component of vision-based driver assistance systems (DAS). Low-level image processing is the first step in such a component. This paper suggests three useful techniques for low-level image processing in lane detection situations: bird’s-eye view mapping, a specialized edge detection method, and the distance transform. The first two techniques have been widely used in DAS, while the distance transform is a method newly exploited in DAS, that can provide useful information in lane detection situations. This paper recalls two methods to generate a bird’s-eye image from the original input image, it also compares edge detectors. A modified version of the Euclidean distance transform called real orientation distance transform (RODT) is proposed. Finally, the paper discusses experiments on lane detection and tracking using these technologies.
28 citations
29 Dec 2011
TL;DR: A realtime and 2D vision-based hand shape recognition method that is robust to hand pose changes because the hand pose is neutralized after recognizing a hand pose using distance transform, principal component analysis (PCA), and histogram analysis.
Abstract: Hand shape is a natural and human-friendly interface for human-computer interaction. This paper proposes a realtime and 2D vision-based hand shape recognition method. The method is robust to hand pose changes because the hand pose is neutralized after recognizing a hand pose using distance transform, principal component analysis (PCA), and histogram analysis. Also, the context-based recognition method using shape decomposition can effectively recognize tiny changes of fingers. The method worked at 44.8 fps and had a recognition rate of 83% on average in the experiment with 800 images including 5 hand shapes and 16 hand poses.
28 citations