Distance transform

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

System and method for verifying registration accuracy in digital medical images

Abstract: A method of verifying a registration of a digital image includes receiving a reference image and a moving image registered to the reference image representing the same object, selecting one or more landmarks in the images, defining a neighborhood in the domain of each image near each selected landmark, extracting feature sets from the neighborhoods for the reference image and the registered moving image, calculating a total quality measure of the registration of the moving image from a distance metric applied to the feature sets extracted from the neighborhoods of the reference image and the registered moving image, comparing the total quality measure to a threshold determined from a reference atlas for the object represented in the image, and determining whether to accept or reject the registration of the moving image based on the comparison result.

Image range finder

Abstract: PROBLEM TO BE SOLVED: To provide a range finder capable of calculating the distance of an object from an infrared image picked up by the image pickup means provided to a vehicle on the basis of the reduced quantity of operation with high accuracy. SOLUTION: The image range finder is constituted so as to calculate the distance from the image pickup means to the object using two infrared images picked up by the image pickup means. The finder is provided with an image dividing means 16 for dividing one image subjected to multiple-valued processing into pattern regions having a predetermined size, a parallax calculation means 17 performing the correlational operation of two infrared images at every pattern region divided by the image dividing means 16 to calculate parallax at every pattern region to convert the same to the distance value of the pattern region, a distance image forming means 18, and a distance value clustering means 20 for classifying the pattern region at every pattern region similar in distance value on the basis of the distance value calculated by the distance image forming means 18 to recognize the same as one group and calculating the distance value of the recognized group to set the same to the distance value up to the object.

Towards representation of 3D shape: global surface parametrization

Abstract: A procedure for the parametrization of the surface of a simply connected object is presented. Starting from a relational data structure describing surface nodes and links to edges and vertices, a distance transform is applied to determine two distant poles. The physical model of a heat conducting surface is then used to obtain latitude and longitude parameters. The net created assigns a unique coordinate pair to each surface node, but its structure depends on the selection of the poles and comprises a systematic nonuniformity of node distributions over the sphere. To correct distortions and to achieve independence of starting conditions, an isotropic non-linear relaxation of the node locations on the sphere is developed. This dynamic modelling procedure is used to obtain the final parametrization.

Surface distance maps

Abstract: We present a new parameterized representation called surface distance maps for distance computations on piecewise 2-manifold primitives. Given a set of orientable 2-manifold primitives, the surface distance map represents the (non-zero) signed distance-to-closest-primitive mapping at each point on a 2-manifold. The distance mapping is computed from each primitive to the set of remaining primitives. We present an interactive algorithm for computing the surface distance map of triangulated meshes using graphics hardware. We precompute a surface parameterization and use the it to define an affine transformation for each mesh primitive. Our algorithm efficiently computes the distance field by applying this affine transformation to the distance functions of the primitives and evaluating these functions using texture mapping hardware. In practice, our algorithm can compute very high resolution surface distance maps at interactive rates and provides tight error bounds on their accuracy. We use surface distance maps for path planning and proximity query computation among complex models in dynamic environments. Our approach can perform planning and proximity queries in a dynamic environment with hundreds of objects at interactive rates and offer significant speedups over prior algorithms.

Method for determining optimal chamfer mask coefficients for distance transform

Abstract: The coefficients of a chamfer mask are, to within a multiplicative scale factor making it possible to give them an integer value, approximations of the Euclidian distances separating the pixels covered by the mask, from the pixel under analysis placed at the center of the mask. As there are at least two possible integer values for each coefficient, the over- and the under-approximation, one is rapidly faced with a considerable number of possible combinations. The method proposed allows progressive selection of the possible integer values, firstly at the level of each coefficient by virtue of an axis error rate criterion, then at the level of the coefficients considered by binomials by virtue of a sector error rate criterion, which considerably reduces the number of combinations to be analyzed to arrive at an optimal combination from the point of view of the error rate obtained in the distance estimations.