Distance transform

About: Distance transform is a research topic. Over the lifetime, 2886 publications have been published within this topic receiving 59481 citations.

Methods for feature-based design of heterogeneous solids

Abstract: This paper presents a parametric and feature-based methodology for the design of solids with local composition control (LCC). A suite of composition design features are conceptualized and implemented. The designer can use them singly or in combination, to specify the composition of complex components. Each material composition design feature relates directly to the geometry of the design, often relying on user interaction to specify critical aspects of the geometry. This approach allows the designer to simultaneously edit geometry and composition by varying parameters until a satisfactory result is attained. The identified LCC features are those based on volume, transition, pattern, and (user-defined) surface features. The material composition functions include functions parametrized with respect to distance or distances to user-defined geometric features; and functions that use Laplace's equation to blend smoothly various boundary conditions including values and gradients of the material composition on the boundaries. The Euclidean digital distance transform and the Boundary Element Method are adapted to the efficient computation of composition functions. Theoretical and experimental complexity, accuracy and convergence analyses are presented. The representations underlying the composition design features are analytic in nature and therefore concise. Evaluation for visualization and fabrication is performed only at the resolutions required for these purposes, thereby reducing the computational burden.

Alignment of three-dimensional protein structures: network server for database searching.

Abstract: Publisher Summary This chapter describes the Dali method, which is a general approach for aligning a pair of proteins represented by two-dimensional matrices. The implementation of prefilters to speed up database searches has enabled us to provide Internet access using World Wide Web. Distance matrices are useful in structure comparison because similar 3-D structures have similar interresidues distances. Imagine a (transparent) distance map of one protein placed on top of that of another protein and then moved vertically and horizontally. In the original Dali method, matches are built up by combining small submatrices with similar distance patterns and using a Monte Carlo algorithm for optimization. The approach was shown to be robust and to yield accurate alignments. This method empirically determined the background strength of similarity as a function of chain length. The statistical significance of a database hit relative to the background is reported as a Z score (score minus mean divided by standard deviation).

Generating compressed light field representation data

Abstract: Systems and methods for the generating compressed light field representation data using captured light fields in accordance embodiments of the invention are disclosed. In one embodiment, an array camera includes a processor and a memory connected configured to store an image processing application, wherein the image processing application configures the processor to obtain image data, wherein the image data includes a set of images including a reference image and at least one alternate view image, generate a depth map based on the image data, determine at least one prediction image based on the reference image and the depth map, compute prediction error data based on the at least one prediction image and the at least one alternate view image, and generate compressed light field representation data based on the reference image, the prediction error data, and the depth map.

Marker-Controlled Watershed for Lesion Segmentation in Mammograms

Abstract: Lesion segmentation, which is a critical step in computer-aided diagnosis system, is a challenging task as lesion boundaries are usually obscured, irregular, and low contrast. In this paper, an accurate and robust algorithm for the automatic segmentation of breast lesions in mammograms is proposed. The traditional watershed transformation is applied to the smoothed (by the morphological reconstruction) morphological gradient image to obtain the lesion boundary in the belt between the internal and external markers. To automatically determine the internal and external markers, the rough region of the lesion is identified by a template matching and a thresholding method. Then, the internal marker is determined by performing a distance transform and the external marker by morphological dilation. The proposed algorithm is quantitatively compared to the dynamic programming boundary tracing method and the plane fitting and dynamic programming method on a set of 363 lesions (size range, 5–42 mm in diameter; mean, 15 mm), using the area overlap metric (AOM), Hausdorff distance (HD), and average minimum Euclidean distance (AMED). The mean ± SD of the values of AOM, HD, and AMED for our method were respectively 0.72 ± 0.13, 5.69 ± 2.85 mm, and 1.76 ± 1.04 mm, which is a better performance than two other proposed segmentation methods. The results also confirm the potential of the proposed algorithm to allow reliable segmentation and quantification of breast lesion in mammograms.

Fixed topology skeletons

Abstract: In this paper, we present a novel approach to robust skeleton extraction We use undirected graphs to model connectivity of the skeleton points The graph topology remains unchanged throughout the skeleton computation, which greatly reduces sensitivity of the skeleton to noise in the shape outline Furthermore, this representation naturally defines an ordering of the points along the skeleton The process of skeleton extraction can be formulated as energy minimization in this framework We provide an iterative, snake-like algorithm for the skeleton estimation using distance transform Fixed topology skeletons are useful if the global shape of the object is known ahead of time, such as for people silhouettes, hand outlines, medical structures, images of letters and digits Small changes in the object outline should be either ignored, or detected and analyzed, but they do not change the general structure of the underlying skeleton Example applications include tracking, object recognition and shape analysis