34 results about "Connected-component labeling" patented technology

The invention discloses a complicated background bar code image automatic partitioning method based on gradient direction consistency. The complicated background bar code image automatic partitioning method comprises the following steps: a first step, converting an input image into a grey image I(n) and calculating horizontal direction gradient Gx(n) and perpendicular direction gradient Gy(n) of each pixel point n on the grey image I(n) to obtain a gradient amplitude G(n) and a gradient angle phi (n) of each pixel point n; a second step, selecting a gradient threshold value alpha, taking the pixel point with the gradient amplitude G(n) larger than the threshold value alpha as an image edge point to obtain an edge image Ie(n); a third step, performing gradient direction consistency estimation and screening based on partitioning to obtain a candidate image block set; a fourth step, calculating an average gradient direction Phici of each candidate image block Pci, and normalizing the average gradient direction Phici to a [-phi / 2, phi / 2] interval as the gradient direction of the candidate image block Pci; a fifth step, performing connected component labeling on the candidate image block based on direction consistency; a sixth step, analyzing and screening a candidate image block connected domain; a seventh step, performing waveform extraction and matching on a candidate bar code region for follow-up decoding. The method disclosed by the invention can identify a bar code more quickly and accurately.

The present invention relates to a method for estimating a measure of a penumbra size of a penumbra in biological tissue wherein first and second images obtained respectively by perfusion weighted imaging (PWI) and diffusion weighted imaging (DWI) are analyzed, and wherein the analysis of the first image includes application of a level set method, and the analysis of the second image includes application of a grayscale morphological operation. In a further embodiment of the invention, a connected component labeling algorithm maybe applied on any one of the first and second image. The invention further relates to a system, a computer program product and use of a corresponding method.

The invention relates to a structure characteristic-based character recognition method. In order to solve defects in the prior art, the technical scheme of the invention comprises the following steps: 1, a serial number area is positioned on an RMB gray scale image, a gray scale image for the serial number is acquired, and tilt correction is carried out; 2, pretreatment is carried out on the gray scale image after tilt correction, a binarization threshold is determined according to a brightness histogram of a target image, binarization processing is carried out on the target image, and a binarization image is acquired; 3, connected component labeling is carried out on the binarization image, and a binarization image of a single character is extracted according to a labeling result; and 4, finally, according to character structure features, the binarization image of the single character is recognized.

The present invention relates to a method for estimating a measure of a penumbra size of a penumbra in biological tissue wherein first and second images obtained respectively by perfusion weighted imaging (PWI) and diffusion weighted imaging (DWI) are analyzed, and wherein the analysis of the first image includes application of a level set method, and the analysis of the second image includes application of a grayscale morphological operation. In a further embodiment of the invention, a connected component labeling algorithm maybe applied on any one of the first and second image. The invention further relates to a system, a computer program product and use of a corresponding method.

The invention discloses an oil stain detection method and an oil stain detection system for bill images. According to the method, acquisition, gray conversion, binarization processing and connected component labeling are performed on the bills in sequence, and stain conditions of the bills are detected further according to the area of a connected component; the system comprises an image acquisition module, a gray image conversion module, a binarization processing module and an oil stain detection module. According to the oil stain detection method and the oil stain detection system disclosed by the invention, manual operation is not needed; the phenomenon that the bill invalidity is caused by the fact that the bills are stained in the automatic processing procedure of batch bills can be effectively solved; the time of manually collating the bills and faults are greatly shortened, and the processing efficiency of the batch bills is promoted. The oil stain detection method and an oil stain detection system disclosed by the invention can be widely applied to bill detection.

The invention discloses a burst point detection system and method based on an FPGA. The system includes a signal control and data processing module, a decoding circuit, a data caching circuit, an Ethernet circuit, and a peripheral circuit. The decoding circuit obtains original image data and caches the original image data to the large-capacity data caching circuit, an improved three-frame difference method in the signal control and data processing module is used to perform burst point target detection to obtain a burst point area, then a gray-scale weighted algorithm is used to obtain center pixel coordinates of a burst point after the connected components labeling, and finally the detected burst point image and the center pixel coordinates of the burst point are sent to a PC via the Ethernet circuit. The system and method of the invention implement the pipeline design of the algorithm steps, obtain high-speed operation results, and can realize the real-time detection of the results ofthe burst point on an image with a resolution of 1024*1024; can accurately obtain the burst point area and can quickly and accurately label the center point coordinates of the burst point; and can still maintain a high detection rate under the premises of light change and background movement.

The invention discloses a laser infrared fusion detection and recognition system, which comprises a nonuniformity correction SoC chip, an image rotation ASIC chip, a multistage filtering ASIC chip, a connected component labeling ASIC chip, a main DSP, a slave DSP, a main FPGA processor and a slave FPGA processor, wherein the slave FPGA processor controls each ASIC / SoC chip to complete laser and infrared image pretreatment; and the main FPGA processor controls the main DSP, the slave DSP and the labeling ASIC to help to complete long-distance, middle-distance and near-distance target fusion detection and recognition. The parallelism and the real-time performance of the system are improved, and power consumption of the system can be effectively reduced.

The present invention provides a side face detecting method and device based on head profile authentication. The method comprises a step of carrying out skin color binary processing on a collected image, carrying out communication component marking on the processed image, and obtaining a plurality of rectangular skin color areas, a step of carrying out hair color binary processing on the areas if the areas satisfy a preset skin color judgment condition, a step of adjusting an interest area according to the areas if the areas satisfy a preset hair color judgment condition, a step of detecting an edge pixel point in the interest area, a step of making a head top profile template according to the interest area, a step of using the template to carry out distribution in the interest area and calculating the edge pixel point quantities in the template in different positions, and a step of taking a quantity maximum value and determining that the rectangular skin color areas have an effective head and side face detection is successful if the maximum value reaches a preset edge pixel value. According to the method and the device, the problem of large angle side face detection is solved, the technical threshold of side face detection is lowered, and the flow of the side face detection is simplified.

A hybrid connected component labeling process for analyzing digitized or binary images includes the following steps. Firstly, a forward scan is executed to assign a forward label to each foreground pixel in the image. Then, a backward scan is executed to assign a backward label to each foreground. The backward labels are rearranged and label connection is recorded. A label allocation table including final labels and reference labels is provided for recording the use of the labels. When an object is considered as noise, the label corresponds to the pixels of the object is released by updating the label allocation table.

The invention discloses a panoramic binary image-based reversal processing method and a panoramic binary image-based reversal processing device, which belong to the field of image processing. The method comprises the following steps of: performing connected component labeling on a panoramic binary image; counting a character height in the panoramic binary image according to labeled connected components; calculating candidate reverse connected components according to the character height; and performing screening according to the upper and lower sidelines of the candidate reverse connected components to obtain reverse connected components, and performing pixel reversal. In the method and the device, the connected components in the panoramic binary image are taken as processing units, the reverse connected components are obtained by performing smoothness screening on the upper and lower sidelines of the connected components, and boundary ranges of the reverse connected components can be accurately calculated for color reversal. The method and the device are not influenced by the thickness of strokes of Chinese characters in the image, greatly improve the reverse connected component positioning accuracy and achieve better image reversal effects.

An input image (e.g. a digital RGB color image) is subjected to an eye classifier that is targeted at discriminating a complete eye pattern from any non-eye patterns. The red-eye candidate list with associated bounding boxes that are generated by the red-eye classifier are received. The bounding rectangles are subjected to object segmentation. A connected component labeling procedure is then applied to obtain one or more red regions. The largest red region is then chosen for feature extraction. A number of features are then extracted from this region. Then these features are used to determine if the particular candidate red-eye object is a mouth.

The present invention discloses a vehicle tracking system and method, and the tracking method comprises the steps of capturing a bright object from an image by the bright object segmentation; labeling the bright object by a connected component labeling method and forming a connected component object; identifying, analyzing and combining the characteristics of the connected component object to form a lamp object by the bright object recognition; tracking the trajectory of the lamp object by a multi-vehicle tracking method; and identifying the type of a vehicle having the lamp object by the vehicle detection / recognition and counting the number of various vehicles.

The invention discloses an automatic crack detection method based on a seismic coherence cube slice and relates to the technical field of petroleum exploration image processing. The method comprises the following steps of (S1) median filtering and denoising, (S2) normalization processing, (S3) bilateral filtering and Laplace filtering processing, (S4) the removal of isolated noise with connected component marking, (S5) morphological operation processing, (S6) the repair of a 2D seismic coherence cube slice with a flood water filling algorithm, (S7) the extraction of a framework by using an FPAalgorithm, (S8) the enhancement of a crack continuity with a MyPadding function, (S9) the marking of the connected component, (S10) processing by using a least squares straight line fitting method, and (S11) classification display including the step of classifying cracks according to the range of different azimuth angles to obtain a final crack automatic detection result of 2D seismic coherence cube slice data. According to the method, the seismic coherence cube slice data can be directly used to extract crack information, the calculation of the azimuth of the cracks is achieved, the crack interpretation efficiency of the seismic slice is greatly improved, and a lot of manpower and material resource costs are saved.

An apparatus for efficient processing of images that are expressed as flows of pixels is disclosed. The proposed pixel flow processor consists of a number of readout units each of them capable of reading images as continuous flows of pixels and flows of pixels provided in bursts, a plurality of pixel flow output units each of them capable of generating images, at least one pixel processing pipeline implementing functions like color conversion, color balancing, scaling and feature extraction, and at least one component labeling unit. This apparatus can be further enhanced with an integral image calculation unit. The apparatus provides output image as continuous flows of pixels and flows of pixels provided in bursts, which can become input to equivalent structures or stored to bus-accessible devices.

The invention provides a method for identifying a serial number on a bill. The method includes the steps that a current identification serial number can be generated from the serial number on the bill according to a binaryzation algorithm, a connected component labeling algorithm, a linear classi er algorithm and a tangent distance algorithm, and the current identification serial number is checked through the other serial number (if the other serial number exists) on the bill and / or a check sum valve corresponding to the serial number on the bill. Thus, the identification accuracy of the serial number on the bill can be effectively improved.

The invention provides a bone joint X-ray film automatic identification and grading method. According to the method, bone joint X-ray film image samples are graded according to a bone joint X-ray filmimage template library, and the bone joint conditions are judged, wherein methods for extracting contour line shape vectors of the bone joint X-ray film image template library and the image samples are same. Firstly, bone joint X-ray film images are preprocessed, and contour lines of key parts of bone joints are extracted by applying wavelet denoising, median filtering and Log edge detection operator methods. Then, the contour lines of the key parts are captured by utilizing a neighborhood feature algorithm, and filtering is performed by adopting a connected component labeling method. Finally, the contour line shape vectors of the bone joint X-ray film image samples are extracted by adopting an improved Fourier descriptor algorithm, the shape vectors of the bone joint X-ray film image template library are matched by a classification algorithm, and the bone joint conditions of the image samples are judged. The bone joint X-ray film automatic identification and grading method can replace manual identification, and is rapid and high in precision.

The invention relates to a run length-based one-scan connected component labeling method and hardware structure. The method comprises the steps of (1) simultaneously scanning two adjacent rows of an input binary image, and recording equivalent run length between the two rows; (2) updating an equivalent run length table after the scanning is completed; (3) detecting a completed connected component,and writing the run length of the completed connected domain into an external memory; and (4) if the current row is the last row, writing all the run lengths in the row and a run length buffer into the external memory, otherwise, repeatedly executing all the steps.

The invention discloses an infrared image target recognition method. The method solves the technical problem of two-dimensional infrared image segmentation by using the concept of one-dimensional image processing, i.e. each row of image pixels for cyclic segmentation processing is synthesized into two-dimensional binary images; and the concrete steps of the method are as follows: firstly, the infrared image enhancement is performed by a multiscale wavelet transformation method; secondly, the stable segmentation of the infrared targets under various imaging conditions is realized by using the extraction to the convex area in the infrared image, and after each row of the pixels is processed, the processing results are synthesized into two-dimensional binary images with sizes consistent withthat of the original images; thirdly, the binary image connected component labeling is performed to the segmented images, meanwhile, the basic characteristics are extracted, then the characteristics to be extracted are defined on the basis, and the characteristic extraction is calculated by using the basic characteristics; fourthly, a candidate target area is determined by a voting method, the accurate recognition is performed by ultimately combining the prior knowledge of the target to be recognized, and the final target is determined from the candidate targets. The invention has the advantages of accuracy, real-time and robustness.

The invention discloses a complicated background bar code image automatic partitioning method based on gradient direction consistency. The complicated background bar code image automatic partitioning method comprises the following steps: a first step, converting an input image into a grey image I(n) and calculating horizontal direction gradient Gx(n) and perpendicular direction gradient Gy(n) of each pixel point n on the grey image I(n) to obtain a gradient amplitude G(n) and a gradient angle phi (n) of each pixel point n; a second step, selecting a gradient threshold value alpha, taking the pixel point with the gradient amplitude G(n) larger than the threshold value alpha as an image edge point to obtain an edge image Ie(n); a third step, performing gradient direction consistency estimation and screening based on partitioning to obtain a candidate image block set; a fourth step, calculating an average gradient direction Phici of each candidate image block Pci, and normalizing the average gradient direction Phici to a [-phi / 2, phi / 2] interval as the gradient direction of the candidate image block Pci; a fifth step, performing connected component labeling on the candidate image block based on direction consistency; a sixth step, analyzing and screening a candidate image block connected domain; a seventh step, performing waveform extraction and matching on a candidate bar code region for follow-up decoding. The method disclosed by the invention can identify a bar code more quickly and accurately.

The invention discloses an online quality inspection method for diamond wire particles based on machine vision. A single-axis mechanical arm is arranged along the moving direction of the diamond wire, a camera and a microscope lens are arranged on the single-axis mechanical arm, and the movement of the mechanical arm and the diamond wire in the same direction reduces the number of cameras. The relative speed difference with the diamond wire improves the clarity of the image. Use the workstation to perform RIO cropping on the original image of the diamond wire, and delete the image area that does not contain the diamond wire information; filter the RIO cropped image to remove the noise of the image; Perform binary segmentation on the filtered image; use morphological closure operation to optimize the image after binary segmentation; use the connected region marking method based on run-length code table search to count the diamond wire particles in the optimized image, and get the diamond wire The statistical data of the particles, the image acquisition and processing can be completed when the diamond wire is moving, and the online quality inspection is realized. The detection speed is fast, and the entire quality inspection process is automatically completed.

The invention relates to a method for marking connected domains, in particular to a method for marking connected domains based on projection transformation. This method takes the binary image as the research object, and uses the projection transformation method to realize the extraction and analysis of the connected regions in the image. The connected domain marking method based on projective transformation realizes the connected domain marking and analysis by projecting the two-dimensional image to the one-dimensional direction, and segmenting and extracting the region according to the projection result. This method uses the idea of ​​projection transformation to transform a two-dimensional region segmentation problem into a one-dimensional line segment segmentation problem, and simplifies the connected domain labeling problem. Compared with the traditional method, the method in this paper is simple to implement and faster to process.

The invention provides a method for identifying a serial number on a bill. The method includes the steps that a current identification serial number can be generated from the serial number on the bill according to a binaryzation algorithm, a connected component labeling algorithm, a linear classi er algorithm and a tangent distance algorithm, and the current identification serial number is checked through the other serial number (if the other serial number exists) on the bill and / or a check sum valve corresponding to the serial number on the bill. Thus, the identification accuracy of the serial number on the bill can be effectively improved.

The present invention relates to a method for estimating a measure of a penumbra size of a penumbra in biological tissue wherein first and second images obtained respectively by perfusion weighted imaging (PWI) and diffusion weighted imaging (DWI) are analyzed, and wherein the analysis of the first image includes application of a level set method, and the analysis of the second image includes application of a grayscale morphological operation. In a further embodiment of the invention, a connected component labeling algorithm maybe applied on any one of the first and second image. The invention further relates to a system, a computer program product and use of a corresponding method.

The invention discloses a laser infrared fusion detection and recognition system, which comprises a nonuniformity correction SoC chip, an image rotation ASIC chip, a multistage filtering ASIC chip, a connected component labeling ASIC chip, a main DSP, a slave DSP, a main FPGA processor and a slave FPGA processor, wherein the slave FPGA processor controls each ASIC / SoC chip to complete laser and infrared image pretreatment; and the main FPGA processor controls the main DSP, the slave DSP and the labeling ASIC to help to complete long-distance, middle-distance and near-distance target fusion detection and recognition. The parallelism and the real-time performance of the system are improved, and power consumption of the system can be effectively reduced.

The invention discloses an automatic detection method for fractures based on seismic coherent volume slices, and relates to the technical field of oil exploration image processing. The invention includes the following steps: S1, median filtering and denoising; S2, normalization processing; S3, bilateral filtering Processing with Laplacian filtering; S4, connected component marking to remove isolated noise; S5, morphological operation processing; S6, flood filling algorithm to repair 2D seismic coherent volume slices; S7, FPA algorithm to extract skeleton; S8, MyPadding function to enhance cracks Continuity; S9, connected component marking; S10, least squares line fitting method processing; S11, classification display, classify fractures according to different azimuth ranges, and obtain the final 2D seismic coherent volume slice data for automatic fracture detection As a result, the present invention can directly use seismic coherent volume slice data to extract fracture information, realize fracture azimuth calculation, greatly improve seismic slice fracture interpretation efficiency, and save a lot of manpower and material costs.

The present invention provides a side face detecting method and device based on head profile authentication. The method comprises a step of carrying out skin color binary processing on a collected image, carrying out communication component marking on the processed image, and obtaining a plurality of rectangular skin color areas, a step of carrying out hair color binary processing on the areas if the areas satisfy a preset skin color judgment condition, a step of adjusting an interest area according to the areas if the areas satisfy a preset hair color judgment condition, a step of detecting an edge pixel point in the interest area, a step of making a head top profile template according to the interest area, a step of using the template to carry out distribution in the interest area and calculating the edge pixel point quantities in the template in different positions, and a step of taking a quantity maximum value and determining that the rectangular skin color areas have an effective head and side face detection is successful if the maximum value reaches a preset edge pixel value. According to the method and the device, the problem of large angle side face detection is solved, the technical threshold of side face detection is lowered, and the flow of the side face detection is simplified.