2291 results about "Gradation" patented technology

The invention discloses a fast monocular vision odometer navigation and positioning method fusing a feature point method and a direct method, which comprises the following steps: S1, starting the vision odometer and obtaining a first frame image I1, converting the image I1 into a gray scale image, extracting ORB feature points, and constructing an initialization key frame; 2, judging whether thatinitialization has been carry out; If it has been initialized, it goes to step S6, otherwise, it goes to step S3; 3, defining a reference frame and a current frame, extracting ORB feature and matchingfeatures; 4, simultaneously calculating a homography matrix H and a base matrix F by a parallel thread, calculating a judgment model score RH, if RH is great than a threshold value, selecting a homography matrix H, otherwise selecting a base matrix F, and estimating a camera motion according to that selected model; 5, obtaining that pose of the camera and the initial 3D point; 6, judging whetherthat feature point have been extracted, if the feature points have not been extracted, the direct method is used for tracking, otherwise, the feature point method is used for tracking; S7, completingthe initial camera pose estimation. The invention can more precisely carry out navigation and positioning.

The invention relates to a tunnel lining crack width measuring method, which comprises the follow steps of: (1) picking up crack images through a digital camera and measuring pickup distance through a laser distance measuring instrument; (2) selecting a region required to be measured on the picked images and converting selected region images into gray level images; (3) determining the threshold value of the gray level images selected in the second step, cutting binary image cutting, and obtaining a target region; (4) extracting a white region only comprising crack in the target region; (5) extracting the edge of the crack by a sub pixel method, and obtaining sub pixel level edge images; (6) circulating the pixel width of the crack by a minimum distance method; (7) circulating the actual width of the obtained crack according to the calibration proportion of the predetermined actual pixel size and the image pickup distance; and (8) storing the obtained actual width data into a crack data base. Compared with the prior art, the tunnel lining crack width measuring method has the advantages of low cost, high speed, convenience, high precision and the like.

The invention relates to a process for the registration of two different images of the same object consisting of breaking down each of the images into space components representing the distribution of the grey levels of the image, applying a phase registration method to the components to bring about a correspondence between the components of one image with those of the other image, summating all the results of the bringing into correspondence and detecting, in the image resulting from said sum, the maximum grey level defining the transformation between the two initial images.

The invention provides an eye precision orientation technology in the field of human face identifying. It is characterized in that it provides an eye precision orientation method on complex background image. It adopts a micro structure character with high efficiency and high redundant to express eye mode local and area grey distributing character and uses AdaBoost computing method to choose the most differential micro structure character to form the strong classer.

The invention discloses an image enhancement and partition method, which comprises the following steps of I, image enhancement: a processor and an image enhancement method based on fuzzy logic are adopted for performing enhancement processing on an image needing to be processed, and the process is as follows: i, converting from an image domain to a fuzzy domain: mapping the grey value of each pixel point of the image needing to be processed to a fuzzy membership degree of a fuzzy set according to a membership function (shown in the specifications); ii, performing fuzzy enhancement processing by utilizing a fuzzy enhancement operator in the fuzzy domain; iii, converting from the fuzzy domain to the image domain; II, image partition: partitioning a digital image subjected to enhancement processing, i.e. a to-be-partition image, according to an image partition method based on a three-dimensional fuzzy division maximum entropy. The method is simple in steps, reasonable in design, convenient to realize, good in processing effect and high in practical value, and an image enhancement and partition process can be simply, conveniently and quickly completed with high quality.

A dynamical image of is an array of black-and-white images, or frames, of arbitrary dimension. Dynamical images are constructed from gray scale and color images, video sequences etc. A method of topological analysis and decomposition of dynamical images through computation of homology groups of the frames is provided. Each frame is partitioned into a collection of components, which, in turn, have tunnels, voids, and other higher dimensional cycles. The cycles in each frame are linked to the cycles in each adjacent frame to record how they merge and split. Further, the dynamical image is simplified by removing from frames all cycles that are small in terms of length, area, volume, etc, or lifespan. Applications of the method lie in image enhancement and restoration, motion tracking, computer vision, surface and curve reconstruction, scientific image analysis, image recognition and matching.

The invention discloses a method for extracting a text in a complex background image. The method comprises the steps of firstly, using the susan operator to detect and identify angular points in a source image, after removing isolated angular points, conducting integral projection transformation to cut out suspected text regions, and screening and removing non-text regions according to priori knowledge; then, judging the background complexity of a text region by the utilization of gray level jump information, when a background is judged to be complex, conducting color clustering on the text region by the utilization of the kmeans clustering algorithm, and determining the type which a text belongs to and extracting the text according to the color information at the position where the angular points are the densest; when the background is judged to be simple, conducting binaryzation on the image by the utilization of a largest-between-class variance method; finally, realizing accurate extraction of the text region. The text extraction method can locate the text region in the complex background image, and finally extracts characters after removing the background.

The invention puts forward an image registration method based on an inertial sensor and a camera. The camera and the inertial sensor are synchronously controlled to operate to simultaneously acquire the color image and depth image of the same scene and the three-axis motion angular velocity and three-axis motion acceleration of the camera; Kalman filtering is utilized to carry out filtering on the three-axis motion angular velocity and the three-axis motion acceleration, the Eulerian dynamics equation is used for converting the three-axis acceleration into a Eulerian angle, the uniformly accelerated motion formula is used for converting the three-axis angular velocity into three-axis displacement, and thereby an external reference matrix of the camera is obtained; by utilizing the affine transformation relation between the color image and the depth image and the proportional relation between depth image grey value and pixel depth information, the depth information of angular points in the depth image is solved; an OFCM (Orthogonal Frequency-division Multiplexing) model is used for calculation to obtain image background optical flow; the RANSAC (Random Sample Consensus) algorithm is used for completing image registration. The calculation load of the method is low, both the real-timeness and the precision are high, and the method is applicable to hand-held devices and mobile devices.

The invention brings forward a rapid and automatic mosaic technology of aerial video in a search and tracking system. The technology provided by the invention comprises the following steps: two continuous frames of color images in an aerial video sequence are converted to grayscale images; three-valued processing is carried out on the grayscale images by an image three-valued method, edge feature information images are extracted by an edge detection sobel operator and feature points are extracted by an Harris algorithm; feature point matching is completed by an optical flow pyramid algorithm; optimal homography matrix of the color images is calculated by combining a DLT algorithm and a RANSAC algorithm; panoramic image mosaics is completed after image correction of the color images by correction geometric transition matrix; and dynamic regulation of image three-valued upper and lower thresholds and a threshold of the edge detection sobel operator is carried out during the process of panoramic image mosaics. According to the invention, image mosaic accuracy and robustness are raised.

The invention relates to a Fourier descriptor and gait energy image fusion feature-based gait identification method. The method comprises the steps of performing graying preprocessing on a single frame of image, updating a background in real time by using a Gaussian mixture model, and obtaining a foreground through a background subtraction method; performing binarization and morphological processing on each frame, obtaining a minimum enclosing rectangle of a moving human body, performing normalization to a same height, and obtaining a gait cycle and key 5 frames according to cyclic variation of a height-width ratio of the minimum enclosing rectangle; extracting low-frequency parts of Fourier descriptors of the key 5 frames to serve as features I; centralizing all frames in the cycle to obtain a gait energy image, and performing dimension reduction through principal component analysis to serve as features II; and fusing the features I and II and performing identification by adopting a support vector machine. According to the method, the judgment whether a current human behavior is abnormal or not can be realized; the background is accurately modeled by using the Gaussian mixture model, and relatively good real-time property is achieved; and the used fused feature has strong representability and robustness, so that the abnormal gait identification rate can be effectively increased.

The invention belongs to the digital image processing field and relates to a processing method for retaining a ghosting-free moving object in high-dynamic range image fusion. The objective of the invention is to remove ghosting and retain a high-exposure degree moving object in an image fusion process. The method includes the following steps that: images are converted into gray-scale images, and histogram equalization is carried out on the series of gray-scale images; with a moving object adopted as a singular point, a modeling result of a moving object-removed background image is obtained by utilizing median filtering; the background image is subtracted from the images comprising the moving object, so that images which only comprise the moving object after the background is removed can be obtained; and through morphological operations comprising erosion and dilation, precision processing is performed on the moving object images, large values are assigned for weight portions corresponding to the pixels of the moving object to be retained by using the coordinate information of the pixels of the moving object to be retained, and an obtained result is adopted as a weight map, and then, fusion is performed on the images according to the weight map. The processing method of the invention is mainly applied to digital image processing.

The invention relates to a method for detecting the color cast of a video image based on Lab chrominance space. The method comprises the following steps: a) converting RGB (Red Green Blue) color space into the Lab chrominance space; b) calculating color cast factors. The invention provides a new color cast detecting factor, which is successively used for detecting the color cast of the image. First, the image is converted from the original RGB color space into the Lab chrominance space; then according to the distinction of the spatial gray level histogram distribution of a chrominance and b chrominance between a normal image without color cast and an abnormal image with color cast, the mean value of the spatial gray level histogram distribution of the a chrominance and the b chrominance are respectively calculated; then according to the statistical distribution between the mean value and the mid value of histograms, the color factors are calculated. A lot of experiments of real street view image databases prove that the new color cast detecting factor disclosed by the invention can really reflect the degree of color cast of images so as to complete color cast detection. The method has the advantages of high detection speed and accurate precision.

The method of fine gradation display by an electro-optical device with little influence by difference in elemental devices, is disclosed, which is an object of the present invention. In case of an active matrix electro-optical device, a visual gradation display can be carried out by digitizing an analog image signal externally supplied by means of binary notation, by temporarily storing the digital signal thus obtained, by outputting the digital signal to a circuit of next step in a proper order, and by controlling the output timing of the signal so as to output the signal to the active matrix electro-optical device, and whereby digitally controlling the time for applying voltage to a picture element.

The invention belongs to the field of recognizing types of vehicles through computer image processing, and relates to a method and system for detecting and recognizing a feature and a brand of a vehicle in a static image by means of a digital picture processing technique. A method for detecting the vehicle in the static image is combined with a vehicle logo detecting method which is based on an AdaBoost framework in the method. The method and system for detecting and recognizing the feature of the vehicle in the static images comprises a training part and a detecting part. The training part includes the following steps of manufacturing a vehicle logo sample, collecting an image containing the vehicle logo from the Internet, positioning the vehicle logo, and extracting the vehicle logo image based on position information; calculating a sample feature, constructing 5 different rectangular features with each rectangular feature corresponding to one Haar feature; training a cascade classifier, inputting the training sample acquired from the last step and conducting training, and finally connecting strong classifiers and multiple corresponding weak classifiers obtained in training in series. The detecting part includes the following steps: loading the image to be detected, converting the image into a grey-scale image and conducting histogram equalization, loading the vehicle logo classifiers which include threshold values of the strong classifiers and the weak classifiers and rectangular feature information corresponding to the selected features, conducting cascade vehicle logo detection with the detected image firstly passing the detection of the former strong classifiers. If the detected image is not the vehicle logo image, the detected image can be excluded at the front end, and only the vehicle logo can finally pass the detection of the strong classifiers at various different levels.

The invention belongs to the technical field of digital image processing and pattern recognition and discloses a general Hough transformation-based method for detecting the position of a traffic signal lamp, which comprises the following steps: by taking an image sequence as input, calculating image gradient information by adopting a first-order differential operator on an image by using image gradation; establishing a traffic lamp shape describing function; defining mapping from an image point to the space of an accumulator; and searching the extreme value of the space of the accumulator to acquire the coordinates of the traffic lamp to provide positional information for traffic lamp state identification. The general Hough transformation-based method for detecting the position of the traffic signal lamp can cope with the significant change of illumination, is insensitive to the influence caused by image sampling color cast and can cope with the traffic lamp with various common shapes.

The present invention discloses a bar code reading method and device. The method comprising an image acquiring step, a barcode positioning step of locating a bar code from an acquired image, and a barcode recognition step of decoding each bar code region to obtain information represented by each bar code. The bar code positioning step, in particular, comprises: dividing the acquired image into a plurality of non-overlapping regions, and calculating a feature score for each region and determining whether the feature score of the region is greater than a feature score threshold Tconfidence, if yes, making the region as useful, otherwise, discarding the area, wherein when the feature score of any region is calculated, the feature score of the region is equal to the sum of the symbolic contrast percentage score, the gray scale histogram peak difference score, the edge-angle histogram peak difference score, and the edge-angle histogram peak-valley area score, and the regions that are marked as useful are combined to obtain a number of merged barcode regions.

The invention belongs to the field of information processing in the information engineering field, and particularly relates to a water surface moving platform visual system image analyzing and processing method. The method includes the steps of image fog removal, graying, image stabilizing, target segmenting, binaryzation, shape characteristic extracting, texture characteristic extracting, establishing of target characteristic bases of different types, and neural network training and testing. The water surface moving platform visual system image analyzing and processing method has the advantages of being high in processing instantaneity, high in image comprehensive analyzing and processing capacity, wide in application range and the like; video image fog removal and electronic image stabilizing can be conducted on a water surface moving platform in real time under the severe weather conditions such as sea fog, and various types of targets on the water surface can be recognized.

The invention provides a multi-target tracking method based on multiple feature combination and a Mean Shift algorithm. The method comprises the following steps S100) a background model is initialized, a background in a video image is updated in a frame difference method, the background is differentiated in a background difference method, and the video image is binarized; S200) denoising and multi-target segmentation are carried out on the binary image sequentially to obtain segmented images with contours of movement targets; and S300) and a multi-target tracking algorithm is carried out on the segmented images on the basis of multiple feature combination and the Mean Shift algorithm. According to the method, features of R, G and B components in a color feature RGB model, H and S components of an HIS model and a gray-scale histogram are tracked comprehensively, the robustness and instantaneity of a target tracking result are improved, and the target sharpness is extracted.

An image forming apparatus includes a control section extracting a color composition of each color ranging from a first to an n^th color from input image data, on the color composition of an m^th color, the m being 1 to n−1, performing a first and a second gamma corrections correcting a gradation of the color composition respectively based on a gamma curve for the m^th color to obtain a first corrected gradation value, and based on a gamma curve for an (m+1)^th color to obtain a second corrected gradation value, and interpolating the first and the second corrected gradation values to determine an output value for the color composition, on the color composition of the n^th color, correcting a gradation of the color composition based on a gamma curve for the n^th color to obtain an output value for the color composition.

The invention discloses an image grey level histogram-based foggy day detection method, which mainly comprises: a first step of performing initialization to obtain a grey level histogram of an image; a second step of primarily detecting whether the image is marked to indicate a foggy day or a fogless day; a third step of performing processing again if the image is marked to indicate the fogless day, and marking the image to indicate the foggy day when a certain condition is met; a fourth step of further performing detection if the image is marked to indicate the foggy day, and marking the image to indicate the fogless day when the certain condition is met; and a fifth step of performing the detection for the third time if the image is marked to indicate the foggy day, marking the image to indicate a densely-foggy day when the certain condition is met, otherwise, marking the image to indicate a thinly-foggy day. In the method, the grey level histogram of the image is utilized to detect weather for the first time, and three levels which are the fogless day, the thinly-foggy day and the densely-foggy day respectively are detected by utilizing corresponding relationships between the number of pixels and grey level values in the grey level histogram and a series of threshold values. Compared with other foggy day detection methods, the method has the advantages of low cost, easy popularization, high processing speed, wide application range, high accuracy and ideal effect.