Topic
Distance transform
About: Distance transform is a research topic. Over the lifetime, 2886 publications have been published within this topic receiving 59481 citations.
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Patent•
AT&T1
TL;DR: An image compression scheme uses a reversible transform such as the Discrete Hartley Transform (DHT) to efficiently compress and expand image data for storage and retrieval of images in a digital format as mentioned in this paper.
Abstract: An image compression scheme uses a reversible transform, such as the Discrete Hartley Transform, to efficiently compress and expand image data for storage and retrieval of images in a digital format. The image data is divided into one or more image sets, each image set representing a rectangular array of pixel data from the image. Each image set is transformed using a reversible transform, such as the Hartley transform, into a set of coefficients which are then quantized and encoded using an entropy coder. The resultant coded data sets for each of the compressed image sets are then stored for subsequent expansion. Expansion of the stored data back into the image is essentially the reverse of the compression scheme.
15 citations
Journal Article•
TL;DR: This correspondence presents systolic algorithms for tasks such as connected component determination, distance transform, and relaxation, which are defined in terms of local operators, which appear particularly appropriate for a VLSI implementation.
Abstract: Les operateurs locaux utilises dans beaucoup de tâches de traitement d'image implique de remplacer chaque pixel dans une image par une valeur calculee a l'interieur d'un voisinage local de chaque pixel. Mise en œuvre d'un circuit VLSI
15 citations
TL;DR: A novel background modeling method focused on dealing with complex environments based on circular shift operator is presented, which is updated with an adaptive update rate to adapt to the background changes.
Abstract: Detecting moving objects in a scene is a fundamental and critical step for many high-level computer vision tasks. However, background subtraction modeling is still an open and challenge problem, particularly in practical scenarios with drastic illumination changes and dynamic backgrounds. In this paper, we present a novel background modeling method focused on dealing with complex environments based on circular shift operator. The background model is constructed by performing circular shifts on the neighborhood of each pixel, which forms a basic region unit. The foreground mask is obtained via two stages. The first stage is to subtract the established background from the current frame to obtain the distance map. The second is to adopt the graph cut on the distance map. In order to adapt to the background changes, the background model is updated with an adaptive update rate. Experimental results on indoor and outdoor videos demonstrate the efficiency of our proposed method.
15 citations
TL;DR: It was found that feed rate of 0.5 ml/h and needle-collector distance of 12 cm is required to generate smooth and uniform hybrid fibers in the smallest size electrospinning with 6 wt.% polymer at voltage of 20 kV.
Abstract: The Canny Edge-Based Distance Transform and Hough Transform algorithms were successfully implemented to analyze the size distribution and the orientation of the electrospun PLA/PBS hybrid fiber. The effect of polymer concentration, voltage, feed rate and needle-collector distance were studied. It was found that feed rate of 0.5 ml/h and needle-collector distance of 12 cm is required to generate smooth and uniform hybrid fibers in the smallest size electrospinning with 6 wt.% polymer at voltage of 20 kV. The stationary flat collector with a swaying needle and fast rotating drum disc with a stationary needle were used for the fiber alignment. In order to improve the size distribution and the orientation of the hybrid fibers it is proposed that the fibers should be collected on the rotary drum disc at 700 rpm or higher speed.
15 citations
TL;DR: Given a large set of unorganized point sample data, a new framework for computing a triangular mesh representing an approximating piecewise smooth surface is proposed, based on the combination of two types of surface representations, triangular meshes and T-spline level sets, which are implicit surfaces defined by refinable spline functions allowing T-junctions.
Abstract: Given a large set of unorganized point sample data, we propose a new framework for computing a triangular mesh representing an approximating piecewise smooth surface. The data may be non-uniformly distributed, noisy, and may contain holes. This framework is based on the combination of two types of surface representations, triangular meshes and T-spline level sets, which are implicit surfaces defined by refinable spline functions allowing T-junctions. Our method contains three main steps. Firstly, we construct an implicit representation of a smooth (C 2 in our case) surface, by using an evolution process of T-spline level sets, such that the implicit surface captures the topology and outline of the object to be reconstructed. The initial mesh with high quality is obtained through the marching triangulation of the implicit surface. Secondly, we project each data point to the initial mesh, and get a scalar displacement field. Detailed features will be captured by the displaced mesh. Finally, we present an additional evolution process, which combines data-driven velocities and feature-preserving bilateral filters, in order to reproduce sharp features. We also show that various shape constraints, such as distance field constraints, range constraints and volume constraints can be naturally added to our framework, which is helpful to obtain a desired reconstruction result, especially when the given data contains noise and inaccuracies.
15 citations