Distance transform

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

Digital auto-focusing apparatus and method

Abstract: An apparatus and method for digital auto-focus are provided. The apparatus includes a local block generator generating a local block from an input image, a distance-estimation unit estimating distances of each image of the local block, a focal-distance-setting unit setting one of the estimated distances of the local block image as a focal distance of the input image, a reblurred-image generator generating a reblurred image from the local block image, a reconstructed image generator generating an in-focus image focused to the estimated distances from the local block image, a local-block-image-matching unit matching the reblurred image to the in-focus image with different weight values based on the set focal distance, and a final-image generator generating a final image by summing the matched local block images.

Method for recognizing a shape from a path of a digitizing device

Abstract: Described is a method for recognizing a shape from a path of a digitizing device. A set of points along a path of the digitizing device is acquired and a parametric representation is fit to the path. The parametric representation is compared to a set of known shapes to determine that the path of the digitizing device represents a particular shape. Fitting the parametric representation to the path includes generating a vector distance field representation of a set of objects corresponding to the set of digitized points, initializing a parametric representation to fit the set of objects, determining a fitting error from the vector distance field representation and adjusting the parametric representation to reduce the fitting error. The fitting error indicates an accuracy of the fit of the parametric representation to the set of objects.

Image fusion based on multi-scale transform and sparse representation: an image energy approach

Abstract: Image fusion is a process to enhance the human perception of different images from the same scene. Nowadays, two popular methods in the signal/image fusion, namely, multi-scale transform (MST) and sparse representation (SR) are being used. This study uses an image energy approach to enhance a fusion rule based on the combination of MST and SR methods. Each source image is first decomposed to its sub-bands using the selected MST method. Then, SR is applied to the low-pass band and maximum absolute (max-abs) rule merges the high-pass bands. The activity level of the sparse coefficients is measured based on the energy differences of the source images. When the gap energy is high enough, a coefficient with maximum L 2 -norm is selected; otherwise, maximum L 1 -norm is considered. Finally, by applying inverse MST to the attained bands, the fused image is reconstructed. The popular MSTs, such as discrete wavelet transform, dual-tree complex wavelet transform and non-sub-sampled contourlet are used. The experiments are carried out on several standard and real-life images. The measurement results confirm that the proposed method has enhanced the contrast, clarity and visual information of the fused results.

Processing apparatus, processing system, processing program, and processing method

Abstract: A processing apparatus includes a distance image acquirer, a moving-object detector, a background recognizer. The distance image acquirer acquires a distance image containing distance information of each pixel. The moving-object detector detects a moving object from the distance image. The background recognizer generates a background model in which a stationary object recognized as background of the moving object is modeled, from the distance image acquired by the distance image acquirer. The moving-object detector changes a method for detecting the moving object, based on a relative positional relation between the moving object and the background model.