67 results about "Distance mapping" patented technology

This invention relates to a system and method for creating an omni-focused image. Specifically, this invention relates to a system and method for electronically amalgamating images using real-time distance information to create an omni-focused image. The system of the invention comprises one or more video cameras aimed at a scene each generating a video output focused at a different distance, a distance mapping camera providing distance information for one or more objects in the scene, and a pixel selection utility wherein the pixel selection utility uses the distance information to select pixels from the video outputs to be used to generate a video display. The system is then operable to focus and amalgamate the video outputs to produce one image with multiple focal points or an omni-focused image.

A method for determining parking availability includes receiving video data from a sequence of frames taken from an image capture device that is monitoring a parking area. The method includes determining background and foreground images in an initial frame of the sequence of frames. The method further includes updating the background and foreground images in each of the sequence of frames following the initial frame. The method also includes determining a length of a parking space using the determined background and foreground images. The determining includes computing a pixel distance between a foreground image and one of an adjacent foreground image and an end of the parking area. The determining further includes mapping the pixel distance to an actual distance for estimating the length of the parking space.

The present invention relates to a method and system for detecting and mapping three-dimensional information pertaining to one or more target objects. More particularly, the invention consists of selecting one or more target objects, illuminating the one or more target objects using a first light source and capturing an image of the one or more target objects, then, illuminating the same one or more target objects using a second light source and capturing an image of the one or more target objects and lastly calculating the distance at the midpoint between the two light sources and the one or more target objects based on the decay of intensities of light over distance by analyzing the ratio of the image intensities on a pixel by pixel basis.

The invention discloses a positioning method and a positioning device based on Bluetooth. The method comprises the following steps of: transmitting a power setting instruction to target Bluetooth equipment, wherein the power corresponding to the instruction reduces gradually; obtaining a power threshold value when the target Bluetooth equipment is out of connection; and matching a preset communication distance mapping table according to the power threshold value, if matching, taking the corresponding distance value as the communication distance corresponding to the target Bluetooth equipment. By obtaining the communication distance from the target Bluetooth equipment, the identification error range of the position of the Bluetooth equipment is greatly reduced and the positioning precision is effectively improved.

A search system (200) for a database (224) including records having a multiple disparate types of media is provided. The search system supports queries, that include different types of search criteria, including content based retrieval search criteria. A fuzzy logic method (400) is provided for effectively combining the results of different types of search criteria. The fuzzy logic method also allows confidence levels entered by the user for search criteria to be considered in combining results. Retrieval relevance values for documents for at least some search criteria are used in the fuzzy logic method. For content based image retrieval searches, the retrieval relevance values are computed by mapping a distance between quantitative characterizations of a search basis image, and other images into a finite range.

The invention discloses an anisotropy diffusion image noise reduction method based on a McIlhagga edge detection operator and belongs to the field of digital image noise reduction. The anisotropy diffusion image noise reduction method based on the McIlhagga edge detection operator is used for restraining speckle noise in an ultrasound image. The anisotropy diffusion image noise reduction method based on the McIlhagga edge detection operator comprises the steps that the McIlhagga edge detection operator with high robustness to noise is used for conducting edge detection on the ultrasound image so that a two-value edge image can be obtained; the two-value edge image is converted into a gradually-varied gray-level edge image through a distance mapping function; the gradually-varied edge image serves as the edge detection operator in an anisotropy diffusion equation, and noise reduction of the ultrasound image is achieved through a numerical solution method with a finite difference in an iterative mode. The method is capable of effectively reducing noise and maintaining the edge and high in robustness under the condition of large noise.

The invention discloses a hyperspectral remote sensing image classification method combined with quick region growth superpixel segmentation. According to the method, superpixels are generated througha region growing method; wherein a distance map is constructed, the generation of superpixels is accelerated; a super-pixel segmentation image and a pixel-based hyperspectral classification image aresubjected to texture adaptive fusion; according to the hyperspectral image classification method, the problem that the classification precision is not high due to the fact that superpixels serve as one unit in a traditional hyperspectral image classification method based on the superpixels is solved, the hyperspectral image classification precision is improved, and the hyperspectral image classification method has important practical significance in the aspects of environment management, crop monitoring, mineral mapping and the like.

The invention discloses a rolling bearing variable-work-condition fault diagnosis method based on visual cognition, and relates to a rolling bearing variable-work-condition fault diagnosis technology. The method comprises the following steps of converting rolling bearing vibration signals under the variable work conditions into a two-dimensional image by using a recurrence plot technology; performing feature extraction on the two-dimensional image by utilizing an SURF (speed up robust features) algorithm to obtain the vision invariability high-dimension fault feature vector; performing dimension reduction processing on the high-dimension feature vector by using an equal-distance mapping Isomap algorithm to obtain the low-dimension stable feature vector; using an SVD (singular value decomposition) algorithm for extracting the feature matrix singular value built by the low-dimension stable feature vector to form the final feature vector; performing fault classification on the final feature vector by using the trained classifier; performing fault diagnosis on the rolling bearing under the variable work conditions. The invention provides a novel solution for the rolling bearing fault diagnosis.

A system and method for detecting a protrusion in a medical image are provided. The method comprises: acquiring a medical image, wherein the medical image is of an anatomical part; segmenting the medical image; calculating a distance map of the medical image; calculating a gradient of the distance mapped medical image; and processing the gradient to detect a protrusion in the medical image. The gradient is processed by: projecting a plurality of rays from a location in the distance mapped medical image; calculating a value for each of the plurality of rays based on features of each of the plurality of rays and the gradient of the distance mapped medical image; summing and scaling the value of each of the plurality of rays; and detecting one of a sphere-like and polyp-like shape using the summed and scaled values of the plurality of rays, wherein one of the sphere-like and polyp-like shapes is the protrusion.

The invention discloses an outdoor unmanned aerial vehicle positioning method and system based on LoRa. The method comprises the following steps: discretizing a signal coverage range of each positioning base station to construct a fingerprint library of a signal RSSI and distance mapping relation, and fitting each positioning base station to obtain corresponding parameters in an RSSI and distancefitting formula; enabling a to-be-positioned unmanned aerial vehicle to send a LoRa data packet with a signal sending timestamp, and after the positioning base station receives the data packet, performing screening according to the arrival time TOA to calculate the average value of RSSI of the qualified data packet; and calculating the distance between the to-be-positioned unmanned aerial vehicleand the positioning base stations according to a fitting formula, and determining the unmanned position by combining the distances between the plurality of positioning base stations and the to-be-positioned unmanned aerial vehicle. According to the invention, TOA and RSSI are comprehensively utilized for positioning, the defects that the error is too large when TOA is utilized for calculating thedistance, and RSSI distance measurement accuracy is easily affected by the environment are overcome, and the positioning precision of the outdoor unmanned aerial vehicle is effectively improved.

A partial response Trellis decoder that performs Trellis coded modulation in a high definition television (HDTV) having a specific and detailed configuration and includes a distance mapper for calculating first, second, third and fourth Euclidean distances between the input signal and a reference value; a Viterbi decoder for Viterbi decoding the first, second, third and fourth Euclidean distances calculated by the distance mapper; a first delay for delaying and outputting the Yiterbi decoded data for each Euclidean distance; a ruler selector for selecting a ruler type signal based on the signals output by the first delay; and a slicer for slicing the selected ruler type signal and the input signal.

The invention discloses a three-dimensional reconstruction method for a light field of a high-reflection surface structure based on point cloud self-adaptive repair. The method comprises the following steps: firstly, building a structured light field three-dimensional reconstruction system, and extracting a multi-view light field sub-aperture image; then, calibrating the reconstruction systemcalibrating , projecting the sine stripe sequence projecting to a reference plane, moving the reference planemoving, recording phase changes recordingon the reference plane under each moving distance through a focusing type light field camera, and subtracting the phase changes from phase values of pixel points at an initial position to obtain a phase difference-depth-of-field (moving distance) mapping relation; reconstructing to obtain a multi-view three-dimensional point cloud through a sub-aperture image extraction algorithm and a mapping relation; and finally, multi-view point cloud data obtained through reconstruction having certain complementarity. A data cavity part in the target point cloud can be iteratively repaired by the same position of other view point clouds, so that complete three-dimensional reconstruction of a high-reflective surface object is realized. In addition, aiming at the reconstruction result, the invention provides a corresponding evaluation method.

Traps are produced at color boundaries in a print page that is present in the form of run-length encoded image data, by way of distance mapping. Distances of the run lengths to an adjacent color are determined without decoding the run lengths into a pixel matrix, and the traps are produced on the basis of the distances thus determined. For this purpose, distance vectors are determined for the starting point and for the end point of a run length. The distance vectors are in each case recalculated from the comparison with the distance vectors of adjacent run lengths. The new values of the distance vectors replace the previous values of the distance vectors if the magnitudes of the distances of the new values are less than the magnitudes of the distances of the previous values.

The invention discloses a sentence distance mapping method and device based on machine learning, computer equipment and a storage medium. The method comprises the steps that input single sentence voice information is acquired; converting the single-sentence voice information into single-sentence text information; preprocessing the single sentence text information, and querying a preset word vectorlibrary to obtain word vectors corresponding to words in the preprocessed single sentence text information; calculating the distance between the single sentence text information and a preset standardsingle sentence by using a preset algorithm according to the word vector corresponding to each word in the single sentence text information; and inputting the distance into a preset function, mappinga score, and training the preset function through training data. Therefore, the similarity between the sentences is accurately calculated, and the technical effect of being more accurate and more visual is achieved.

A three-dimensional ultrasonic inspection apparatus includes: an ultrasonic transducer disposed m×n piezoelectric vibrators in a matrix; a signal processing device to receive, detect an echo, and generate a three-dimensional image data by processing an electric signal of the echo detected; and a display processing device to display a result of processing the three-dimensional image data generated by the signal processing device, wherein the display processing device includes a peak detecting unit to detect a first peak and a second peak of an intensity distribution of the three-dimensional image data in a depth (z) direction, a joint portion image creation unit to create a three-dimensional image of the joined area by mapping z direction distance of the first peak and the second peak to x-y plane, a determination unit to determine whether the joined area is sound or not, and a display unit to display the three-dimensional image and the determination result of the joined area.

The invention relates to a spatiotemporal delay correlation visualization method. The method comprises the steps of representing a correlation of different delay time through continuous rectangular blocks mapped by different colors based on a rectangle-based visualization method; and representing a correlation of sites with different spatial relationships through hierarchical division and distance mapping of rectangular bands (a plurality of rectangular blocks corresponding to each site). Through the method, the delay correlation of multiple pieces of time series data with spatial relationships can be visualized, thereby assisting an analyst to discover a causal relationship implied in the correlation.

The invention relates to a distance mapping pattern classification method. The established distance mapping classifier comprises four parts, namely an input layer, a hidden layer 1, a hidden layer 2 and an output layer. The input layer comprises d neuron nodes, and each node represents a feature vector of a training or test sample. The feature vector set of the extracted samples is used as the input layer of the distance mapping classifier. The hidden layer 1 contains N neuron nodes, N representing the total number of training samples; and calculates the Euclidean distance between the input eigenvector and the eigenvectors of N training samples as the hidden layer 1. The hidden layer 2 consists of L neuron nodes. The hidden layer 1 and the hidden layer 2 can be connected by linear activation function. The two parameter matrices of the linear activation function are the connection weights and offsets of the hidden layer 1 and 2 respectively. When the classifier model is used to classifythe test samples, the output matrix can be calculated directly by using the transformation matrix obtained from the training.