192 results about "Image differencing" patented technology

Monitoring systems, devices, and methods for monitoring one or more objects within an environment are disclosed. An illustrative monitoring device in accordance with the present invention can include an image detector, an on-board image processor, and communication means for transmitting an imageless signal to a remote location. The image processor can be configured to run one or more routines that can be used to determine a number of parameters relating to each object detected. In some embodiments, the monitoring device can be configured to run an image differencing routine that can be used to initially detect the presence of motion. Once motion is detected, the monitoring device can be configured to initiate a higher rate mode wherein image frames are processed at a higher frame rate to permit the image processor to compute higher-level information about the moving object.

A method for determining a parking violation includes receiving video data as a sequence of frames provided by a camera. The method includes defining a location of an exclusion zone in the video data. The method includes detecting a vehicle located in the defined exclusion zone. The detecting includes determining a background in an initial frame of the video data and determining a background in a select frame by applying a predetermined updating process. The detecting includes subtracting the background of the select frame from the initial frame to obtain an image difference. The detecting includes classifying the pixels in the image difference as foreground or background pixels and classifying the pixels in the foreground image as vehicle or non-vehicle pixels. The method includes determining a duration that the detected vehicle is in the exclusion zone based on a number of the sequence of frames including the detected vehicle.

A method and apparatus are disclosed for testing the accuracy of digital test images generated by a computer graphics program executed on a computer graphics system. A test program is utilized to compare the test image with a reference image. The user defines regions of interest and a maximum error for each region. This allows the user to focus on a particular object or group of objects. Global image quantification verification generates one measurement of error or image difference for each region of the test image. Each region is divided into sub-regions and an average color value is calculated for each sub-region and the corresponding sub-region in the reference image. The differences between the averages for corresponding sub-regions in the test and reference images are calculated. A test image region may be unacceptably different from a reference image if a normalized sum of the absolute differences exceeds the maximum error.

The invention discloses a camera lens occlusion detecting system and method. The system comprises an image collection module, an image pre-processing module, a background establish module, a high-frequency component extraction module, a generalized image establish module, a suspected occlusion area detection module and an occlusion area determining module, wherein the background establish module is used for acquiring a smooth background image; the high-frequency component extraction module differentiates an initial image and the background image to acquire a high-frequency component distribution graph; the generalized image establish module combines an enhanced image and a pre-processed initial image to establish a generalized image, and performs edge extraction on the generalized image and the generalized image is convolved; the suspected occlusion area detection module compares a convolution result with a preset threshold, and determines that the suspected occlusion area is a candidate occlusion area if the convolution result is less than the preset threshold; and the occlusion area determining module traces the subsequent image pixel value of the suspected occlusion area, and determines that the suspected occlusion area is an occlusion area finally if brightness variations of all the pixels in the area are less than the preset threshold. By using the system and the method, whether the lens is occluded or not can be effectively judged.

The invention relates to the field of internet electronic commerce, in particular to a commodity similarity calculation method and a commodity recommending system based on image similarity. The method includes: preprocessing a target image, to be specific, removing image differences caused by changes in light conditions such as brightness and chromatic aberration; processing the target image to detect a foreground frame; converting a community image in the foreground frame into pixel images different in scale by means of bilinear interpolation, and acquiring attribute features, in different dimensions, of the commodity image in the foreground frame under different scales; calculating attribute feature similarities, under different scales, between an attribute feature vector of the commodity image in the foreground frame and an attribute feature vector of a commodity sample image; according to a decision forest model and the attribute feature similarities under different scales, calculating commodity image similarities, under the pixel images of different scales, between the commodity image in the foreground frame and the commodity sample image; using the commodity image as a uniform identifier of a commodity on different commercial platforms. The commodity similarity calculation method and the commodity recommending system have the advantage that reliability of the system is greatly improved.

An autonomous navigation, guidance, and control process for docking and formation flying by utilizing the laser dynamic range imager (LDRI) and key technologies, including fuzzy logic based guidance and control, optical flow calculation (including cross-correlation, phase-correlation, and image differential), software design and implementation, and verification methods. The autonomous navigation, guidance, and control process includes the steps of providing an expected reference position relative to a target; generating a carrier position and attitude relative to said target by a Range and Intensity Images Provider; producing a relative position and attitude error; and producing control commands from said relative position and attitude error for relative motion dynamics.

The invention discloses an edge finding cutting method of a laser cutting device which is characterized in that images of an object needing to be cut are collected through a camera. A correcting document is used for the correction to generate a contour graph. Then, based on the contour graph, a matching model is constructed. Then, the patterns cut in real time are collected through the camera according to set parameters. The vectorization treatment is implemented on the collected images to generate graphs. The graphs are compared with the matching model according to the set similarity. An image satisfying the set similarity is the successful matching image. To the successful matching image, cutting data are generated according to the contour graph of the actually paragraphed image. Finally, the cutting data are sent to the laser cutting device to be cut. The cutting method is characterized by automatically adapting to the cut image differences within certain similarity scope and realizing the precise cutting of images.

A projector includes an image distortion sensing section which generates image distortion sensing information, an environmental influence sensing section which generates environmental influence sensing information, a projection area information generation section which generates projection area information, an image distortion correction section which corrects distortion of a projection image and generates correction information indicating the degree of correction, a display area information generation section which generates display area information indicating the display area of the projection image after distortion correction based on the projection area information and the correction information, an environmental influence reduction section which performs processing of reducing environmental influence, a projection section which projects the projection image, and a differential image generation section which generates a differential image.

Methods, apparatuses, and systems are presented for measuring difference between graphics images relating to performing an arithmetic operation involving a first graphics image comprising a plurality of first pixels and a second graphics image comprising a plurality of second pixels to produce a difference image comprising a plurality of difference pixels, generating measures of proximity from a plurality of ranges of observation within the difference image, wherein the measures of proximity represent spatial proximity of difference pixels to other difference pixels within the difference image, and applying non-uniform weighting to the difference pixels to produce a weighted difference image, wherein the non-uniform weighting depends on the measures of proximity generated from the plurality of ranges of observation.

Methods and apparatus for performing stereoscopic image encoding and decoding are described. Left and right eye images are generated. Image difference information is generated, e.g., a set of pixel values resulting from XORing the pixel values of the left and right eye images. One of the left and right eye images is compressed along with the difference map. The compressed image and compressed difference map is stored and / or transmitted. Stereoscopic images are generated by decompressing and using the received compressed image and compressed difference information. Prior to generation of the difference map the left and right eye images may be subject to a transposition operation to minimize the differences between the images and thus the size of the difference map. When transposition is applied, transposition information is stored and communicated in addition to the compressed image data so that the transposition can be reversed during the stereoscopic image generation process.

A system automatically compares radiotherapy 3D X-Ray images and subsequent images for update and re-planning of treatment and for verification of correct patient and image association. A medical radiation therapy system and workflow includes a task processor for providing task management data for initiating image comparison tasks prior to performing a session of radiotherapy. An image comparator, coupled to the task processor, in response to the task management data, compares a first image of an anatomical portion of a particular patient used for planning radiotherapy for the particular patient, with a second image of the anatomical portion of the particular patient obtained on a subsequent date, by image alignment and comparison of image element representative data of aligned first and second images to determine an image difference representative remainder value and determines whether the image difference representative remainder value exceeds a first predetermined threshold. An output processor, coupled to the image comparator, initiates generation of an alert message indicating a need to review planned radiotherapy treatment for communication to a user in response to a determination the image difference representative remainder value exceeds a predetermined threshold.

A method for producing an improved high resolution image is disclosed including capturing low resolution images and a high resolution image; combining the low resolution images to provide an aggregate low resolution image; reducing the resolution of the high resolution image and then interpolated to produce a blurred high resolution image; calculating an image difference map using the aggregate high resolution image and blurred high resolution image; and using the image difference map along with the aggregate high resolution image and the high resolution image to produce an improved high resolution image.

The invention provides an image processing apparatus comprising: an acquisition unit configured to acquire a plurality of captured images captured by an image capturing apparatus; a determination unit configured to determine position information of the image capturing apparatus for each of the plurality of captured images so that an evaluation value becomes smaller; and a connecting unit configured to connect the plurality of captured images projected onto a reconstruction plane using the determined position information of the image capturing apparatus, wherein the determination unit comprises a calculation unit configured to project each of the plurality of captured images onto the reconstruction plane based on the set position information and to calculate, as the evaluation value, an image difference between the projected images in a overlapping region between the projected images.

The present invention is directed to a method of processing an ultrasound image, comprising the steps of: a) successively acquiring ultrasound images from an object; b) sampling ultrasound images in a predetermined time interval; c) determining an image difference between a currently sampled ultrasound image and a previously sampled ultrasound image; d) if the image difference is greater than a critical value, adjusting image parameters to optimize the image parameters; and e) applying the adjusted image parameters to the ultrasound images.

A method and apparatus are disclosed for testing the accuracy of digital test images generated by a computer graphics program executed on a computer graphics system. A test program is utilized to compare the test image with a reference image. The user defines regions of interest and a maximum error for each region. This allows the user to focus on a particular object or group of objects. Global image quantification verification generates one measurement of error or image difference for each region of the test image. Each region is divided into sub-regions and an average color value is calculated for each sub-region and the corresponding sub-region in the reference image. The differences between the averages for corresponding sub-regions in the test and reference images are calculated. A test image region may be unacceptably different from a reference image if a normalized sum of the absolute differences exceeds the maximum error.

An adaptive halftoning method where the difference between a digital image and a filtered digital image is introduced into the system on a pixel by pixel basis is disclosed. In this method, each input difference pixel has a corresponding error value of the previous pixel added to the input value at a summing node, resulting in modified image difference data; the modified image difference data is passed to a threshold comparator where the modified image difference data is compared to a threshold value, the threshold value varying according to the properties of the digital image, to determine the appropriate output level; the output level is subtracted from the modified image difference value to produce the input to an error filter; the output of the error filter is multiplied by an adaptation coefficient, where the adaptation coefficient varies according to the properties of the digital image, to generate the error level for the subsequent input pixel; and, the cyclical processing of pixels is continued until the end of the input data is reached.

A method for identifying a person from the detected eye image has been developed, the steps of which are: (a) discriminating the image difference by comparing the detected personal eye image with the simple background scene, and compressing the corresponding discriminated eye image; (b) decoding the compressed image to the binary coded image by utilizing multi-critical values; (c) defining only the bright region of the binary coded image as the surveying area; (d) generating the histogram for the surveying area; (e) comparing the specified histogram of the surveying area with various pre-stored templates to sort-out the similar facial groups and pick at least one similar eye region among the similar facial groups, and (f) determining the best matched eye appearance through the character analysis of the selected similar eye regions.

The invention provides a security and protection monitoring system and a corresponding warning triggering method of the system, wherein the method comprises the following steps that a first processor obtains a first signal representing that an infrared sensor is triggered; a first lens is controlled to shoot a first image according to the first signal; a stored first background image is obtained; the differences between the first image and the first background image are compared; if the differences meet a preset condition, first warning operation is triggered. The mode of simultaneously utilizing the infrared sensor detection and the image difference detection is adopted, so the probability of false alarm caused by higher environment temperature can be reduced.

The invention provides a weighted local entropy infrared small target detection method based on multi-scale morphological image fusion, and the method comprises the steps: firstly, converting an infrared image into a gray domain, and carrying out the processing; secondly, performing multi-scale morphology Top-Hat image segmentation processing on the infrared image; solving image difference on thebasis of adjacent scale Top-Hat and obtaining minimum difference graph is obtained, and then comparing the minimum difference graph with a minimum mean value image of the image subjected to Hat transformation to obtain an image subjected to background suppression; then, obtaining a local entropy information graph by calculating the local entropy of the initial image; then, carrying out dot multiplication on the image subjected to background suppression and the local entropy information graph, and carrying out normalization to obtain a saliency map of the infrared small target; and finally, filtering and binarizing the infrared small target saliency map by using a threshold segmentation technology to obtain a processed image, the region with the binarized value of 1 being the infrared smalltarget. The method is suitable for the field of infrared small target detection, can effectively improve the accuracy of infrared small target detection, and effectively reduces the false alarm rate.

A system and method accelerates update of a metadata search database using PCPI differencing. After first populating the search database, a search agent generates a PCPI and utilizes a PCPI differencing technique to quickly identify changes between inode files of first and second PCPIs. The differences are noted as modified metadata and are written to a log file, which is later read by the search agent to update the search database.

An image checking process wherein only a defective or differential portion of a checked image is displayed together with its position and wherein no pre-processing is required for image positioning. A computer (3) captures a reference image or Fourier transformed image thereof from a storage part, a CCD camera (1) or a CCD camera (2) to acquire intensity information and phase information, and also captures an identified image or Fourier transformed image thereof from the storage part, CCD camera (1) or CCD camera (2) to acquire intensity information of the Fourier transformed image of the identified image. Then, the computer (3) determines the difference in intensity information between the reference image and the Fourier transformed image of the identified image and further determines an inverse Fourier transformed image of an expression obtained from the determined differential intensity information and the phase information of the reference image to output the inverse Fourier transformed image to an output part or display part. The inverse Fourier transformed image is used to extract, as a difference between the identified image and the reference image, an image defect of the identified image or the image difference between the identified image and the reference image.

The invention discloses a small bearing quality detection method, device and system based on machine vision, wherein the method comprises the steps of S1, judging whether a to-be-detected small bearing exists in a to-be-detected region, and if yes, skipping to the step S2; S2, collecting an image of a small bearing; S3, matching the template images in a database according to the collected images; S4, obtaining an image difference between the collected image and the matched template image through an image frame difference method, and analyzing the image difference to determine whether a defect region exists or not; and S5, controlling the small bearing to be conveyed to a corresponding discharging rail. According to the present invention, the small bearing quality detection, the automatic feeding and the automatic removing based on the machine vision are achieved, so that the accuracy is improved, and the purpose of rapid and automatic detection is achieved.

The invention relates to a vehicle abnormal deceleration region detecting method and a vehicle abnormal deceleration region detecting system based on trajectory data. The vehicle abnormal decelerationregion detecting method refers to an image differential anomaly detection method commonly used in machine vision, performs analysis and clustering on historical trajectory data, constructs an ''imagebackground'' of a road section deceleration region, compares a deceleration confidence region with a deceleration region based on real-time data clustering, and highlighting an abnormal decelerationregion of the road section. The vehicle abnormal deceleration region detecting method and the vehicle abnormal deceleration region detecting system overcome the problems of low patrol efficiency and high delay of the traditional road network traffic events, can provide data support for the traffic department to maintain normal operation of the traffic system, shorten the discovery time of the roadabnormal event, reduce the labor cost, can push anomaly information to drivers near the abnormal deceleration region by means of communication software, realize the timely induction of vehicles and avoid the occurrence of large-scale congestion.

The invention belongs to the image fusing field, and specifically relates to an infrared polarization and light intensity image fusing method guided by a multi-feature objective function capable of comprehensively considering difference feature types and strong-weak relationship of a source image at several aspects and increasing the feature utilizing rate to improve the fusion effect. According to the invention, by utilizing the type and the amplitude of infrared polarization and light intensity image difference feature and an objective function established by a fusion weight vector, the strong-weak relationship between pixel multiple attributes is comprehensively considered; by utilizing features between source images as difference information between individuality of a group and by utilizing differential evolution to perform optimization fusion based on group differences, the fusion pertinence and the fusion effect of each feature are improved; the method has the several features of effectively improving the grey level, the texture, the edge and the contrast ratio in a fused imaged. The method is mainly used to fuse infrared polarization and light intensity images.

The invention discloses a method and device for obtaining an image diversity factor result. The method includes the steps: obtaining a color diversity factor value and a structure diversity factor value of pixels in each same position by comparing the color similarity and the structure similarity of pixels in the same position in a first image and a second image; obtaining offset of each pixel through calculation and according to the color diversity factor value and the structure diversity factor value, and calculating an offset consistence diversity factor value of any pixel according to the offset of each pixel; obtaining diversity factor value results of the two images according to the color diversity factor values, the structure diversity factor values and the offset consistence diversity factor values. According to the method device for obtaining the image diversity factor result, improvement of precision of the image difference detection results is achieved.

A method of creating an image difference overlay comprises identifying a loop of reference images of a subject and identifying a loop of data images of the subject. The loop of image data can be identified after an event, such as the administration of contrast agent to the subject. A reference loop image frame is compared to one or more data loop image frames and the reference loop frame is associated with a data loop image frame which closely resembles the data loop image frame. Each of the associated frames can then be processed and used to create an image difference overlay frame.

A method for producing an improved high resolution image is disclosed including capturing low resolution images and a high resolution image; combining the low resolution images to provide an aggregate low resolution image; reducing the resolution of the high resolution image and then interpolated to produce a blurred high resolution image; calculating an image difference map using the aggregate high resolution image and blurred high resolution image; and using the image difference map along with the aggregate high resolution image and the high resolution image to produce an improved high resolution image.

The invention relates to a video handwriting character inputting device and a method thereof. The device comprises an image capturing unit, an image processing unit, a one-dimensional characteristic encoding unit, a character database storing Chinese, English, numbers and symbols, a character identifying unit and a display unit. The method comprises the following steps that: the image capturing unit captures an image; the image processing unit filters a motion track of a fingertip in the image by performing difference detection and then skin color detection on the image and selecting the motion track which is best matched with a point of a target object; the one-dimensional characteristic encoding unit extracts strokes of the motion track and converting the strokes into a one-dimensional serial encoding sequence according to a time sequence; and the character identifying unit compares the characters in the one-dimensional serial encoding and the character database, finds the characters with the highest similarity degree and outputs the found characters on the display unit.