336 results about "White area" patented technology

A system and method for processing data representative of a color image is disclosed. Image data represents an intensity of photoexposure of an imaging array at specific locations in the imaging array and in distinct spectral regions corresponding to color channels. A process identifies “white” regions in the color image by comparing the intensities of photoexposure of groups of associated pixels which are responsive to photon energy in different spectral regions. If the intensities of photoexposure of the pixels in the group of associated pixels are proportionally equivalent, these pixels are determined to be in a white region of the image. White balancing gain coefficients are then based upon the pixel intensity values at pixel locations in the white regions of the image.

The invention relates to a method and a device for displaying image by reducing power consumption. On the basis of little appearance opportunity of a large high-brightness pure white area in an image, an image analyzer is additionally provided on the basis of the prior projection display system, image data is analyzed by using a frame as a unit so as to ensure a multiplication number of various kinds of fundamental color data, control signals which are relative to the image data and the multiplication number are output to a light source so as to reduce and regulate the output power of fundamental color light beams, the fundamental color data of the image data can be correspondingly controlled, magnified and regulated, and thereby under the premise that the display image is not affected inthe brightness and the contrast ratio, the power consumption of the projection display system is greatly reduced. The display contrast ratio of the system can be improved by adopting the method and the device for displaying image and an LED light source.

A scanner for obtaining an image of an object placed on an at least partially transparent platform, wherein the platform is defined by edge portions and has at least including a first scan area and a second scan area. In one embodiment, the scanner includes a white area formed at least partially around the edge portions of the platform with a plurality of markers, optical means for sequentially scanning consecutive partial images of the object from the first scan area and the second scan area, respectively, wherein each of the consecutive partial images include an image of at least one of the plurality of markers, and an image processing system for using the image of the at least one of the plurality of markers in each of the consecutive partial images as a reference to combine the consecutive partial images so as to form a substantially complete image of the object corresponding to a full scan of the first scan area and the second scan area.

A method for selecting two different light-emitting materials for use in an OLED device, each of which produces different color light, which combine to produce white light. Each light emitting material has its own point on a chromaticity diagram, and the light-emitting materials are selected such that, when a line is drawn between the first point and the second point, it passes through a desired white area defined on a chromaticity diagram.

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 provides a cloud atlas segmentation method based on a FCN and a CNN, and belongs to the field of image segmentation of computer vision. The method is characterized in that firstly, a near neighborhood of each pixel point in a cloud atlas is correspondingly clustered through an ultra-pixel, the cloud atlas is input to fully convolutional networks FCN32s and FCN8s with different step lengths, and pre-segmentation results of the cloud atlas are realized; in a FCN32s result map, a black area is a part of a non-cloud area in the cloud atlas, and in a FCN8s result map, a white area is a part of a cloud area in the cloud atlas; and remaining uncertain areas are grey areas which need to be determined through a deep convolutional neural network (CNN), key pixels in an ultra-pixel area need to be selected to represent characterizes of the ultra-pixel area, and whether the characteristics of the pixels are cloud or non-cloud is determined through the CNN network. According to the method, the precision is equivalent to that of MR-CNN and SP-CNN, and the speed is increased by 880 times compared with MR-CNN and increased by 1.657 times compared with SP-CNN.

The invention discloses a video-analysis-based smoke detecting method, which is realized by taking a digital camera as a sensor and under support of a digital signal processing chip. The method is characterized by comprising the following steps: collecting digital video by utilizing the digital camera; screening out a foreground part containing a movement part; screening out an area with likeness by using a support-vector-machine detector; analyzing high-frequency signal change by applying wavelet transform, and screening out a digital image of which the background is in gradually fuzzy change; and screening out digital images with smoke texture characteristics by using an Adaboost cascade classifier pairs. By combining moving object extraction by background modeling, grey area screening by a support-vector-machine (SVM) classifier, high-frequency signal change analysis by wavelet transform, the smoke texture characteristic cascade classifier and other methods, the method greatly improves the accuracy and efficiency of smoke detection, reduces the false alarm rate and has high robustness and higher practicality.

A scanner for obtaining an image of an object placed on an at least partially transparent platform, wherein the platform has at least a first scan area and a second scan area. The scanner includes a white area formed at least partially around the edge portions of the platform with a plurality of markers, one rotatable mirror, one or more image sensors. In scanning, each partial image from each of the scan areas includes an image of at least one portion of the plurality of markers. An image processing system uses the image of the at least one portion of the plurality of markers in each of the consecutive partial images as a reference to combine the consecutive partial images so as to form a substantially complete image of the object corresponding to a full scan of the first scan area and the second scan area.

A system, method and search engine for searching images for data contained therein. Training images are provided and image attributes are extracted from the training images. Attributes extracted from training images include image features characteristic of a particular numerically generated image type, such as horizontal lines, vertical lines, percentage white area, circular arcs and text. Then, the training images are classified according to extracted attributes and a particular classifier is selected for each group of training images. Classifiers can include classification trees, discriminant functions, regression trees, support vector machines, neural nets and hidden Markov models. Available images are collected from remotely connected computers, e.g., over the Internet. Collected images are indexed and provided for interrogation by users. As a user enters queries, indexed images are identified and returned to the user. The user may provide additional data as supplemental data to the extracted image data. A chart, representative of the supplemented data, may be generated and provided to the user in response to a particular query.

The invention provides a method and equipment for identifying a two-dimension code, and relates to the field of an image identifying technique. The equipment is capable of improving the accuracy rate of a location detection graph for locating the two-dimension code, so as to improve the success rate of identifying the two-dimension code. The method comprises the steps of determining n centers of gravity of n first areas, wherein n first areas are overlapped areas of a horizontal area and a vertical area in a two-dimension code image to be identified, the horizontal area is an area of which the proportion of the width of a black area to the width of a white area in the horizontal area is a first preset proportion, and the vertical area is an area of which the proportion of the width of a black area to the width of a white area in the vertical area is the area of the first preset proportion; determining the center of gravity of the location detection graph in n centers of gravity; detecting the center of gravity of the location detection graph of the two-dimension code as a first seed point for region growing, so as to form an area where the two-dimension code is; and obtaining the information of an image where the two-dimension code is. The method is applied to a two-dimension code identifying system.

Background removal processing applies image processing indiscriminately to the whole image on the basis of an assumed presence of a background. Therefore, if the input image has a background and the luminance tone level of this background is relatively low, the background area cannot be removed.It is made possible to scan a document with a color scanner 40 and determine a blank paper area constituting the background of the document image, i.e. a substantially white area, according to a prescribed frequency distribution of image data constituting the image. It is further made possible to provide clear contrast between the background of the image reproduced from image data and the non-background part of the image and to remove noise components appearing on the background, such as what is written or drawn on the wrong side of paper seen through, because, once the presence of a background is determined, the substantially white background area is retouched to white, i.e. the highest tone, by image data retouching according to a correction curve.

The quality of the reproduced image in separating the character portions and the areas near or surrounding the character portions has been improved. In particular, as the result of the character edge enhancement, the possibility for mistakenly processing white areas around the character edges has been substantially reduced and the correct detection rate for character edges in high line density areas has been substantially increased.

The invention relates to a white balance processing method directed towards an atypical-feature image. The method comprises the following steps: (1) acquiring the brightest spot RGB (Red, Green and Blue) information of a frame of images as well as an RGB mean through a Camera Link industrial camera; (2) scanning the frame of video images, setting a white spot brightness threshold value and an RGB channel difference threshold, and determining whether current images contain a white area or not and color is rich or not; (3) performing color space conversion on the current images if the current images are determined that the white region is not contained and the color is not rich, and respectively calculating an average chromaticity Cw_ave of a reference point of a perfect reflection method and an average chromaticity Ch_ave of a reference point of a gray world method; and (4) calculating an average chromaticity Cw_ave obtained by the perfect reflection method and an average chromaticity Ch_ave obtained by the gray world method directed towards the current images, and performing white balance correction combined with two classic algorithms on the current frame of images by using the ratio of the Cw_ave and (the Cw_ave plus the Ch_ave) as an adjustment factor K. The method can be realized by using the recourses of an FPGA (Field Programmable Gata Array) internal logic unit, an internal memory, a multiplier and the like.

The invention relates to a white balance processing method and device and a computer device. The method includes the following steps: conducting face recognition on an image to recognize a face area and a background area except the face area; obtaining a reference area in the face area, wherein the reference area is a white area in an object; performing white balance processing on the whole image on the basis of the reference area or performing white balance processing on the face area on the basis of the reference area; and performing white balance processing on areas except the face area according to the background area. White balance processing can be conducted on the image according to the specific reference area in the face area of the image, so the white balance accuracy is increased, and the user experience is improved.

There is provided a method of controlling auto white balance that can be appropriately used for a camera of an electric device that uses a wide-angle or a super wide-angle lens. A method of controlling auto white balance according to an aspect of the invention may include: converting a color space of an input image from an RGB color space into a YCbCr color space; dividing the input image into a plurality of divided regions; selecting a predetermined number of divided regions in order determined by mean values of Y of pixels included in the plurality of divided regions; comparing a predetermined threshold value with the number of pixels having values of Cb and Cr within a predetermined Cb-Cr range among the pixels included in the selected divided regions in order to determine a white area; and calculating auto white balance gains by using mean values of Y, mean values of Cb, and mean values of Cr of the pixels included in each of the selected divided regions when the number of pixels within the predetermined Cb-Cr range is greater than the threshold value.

The invention provides a color keeping based real-time video defogging method in order to effectively recover the contrast and color of an image / video in hazy weather in real time. The method comprises the following steps: firstly, using an optimized orientated filtering method to give a parameter self-adaptive selection method; secondly, providing a simple and effective method to correct the situation that dark channel prior is not suitable for the sky and other large-area white regions; providing a self-adaptive brightness adjustment method capable of keeping the color of an object in order to solve the dark problem of the defogged image, so that the image is realer and more natural; finally, in order to process high-resolution images in real time, adopting a downsampling method for a part with improved transmissivity so as to increase the speed. The time complexity of the algorithm provided by the invention is only a linear function of the number of image pixels, the processing speed is quick, and the consumed time is 80ms for an image with resolution of 600 x 400. The method provided by the invention provides a powerful competitive advantage for enhancing the performances of digital and monitoring products, and provides a core competitive advantage for carrying out the development of video processing chips and intelligent surveillance products and other fields.

The present invention is a method of processing a digital image that is initially represented by digital data indexed to represent positions on a display. The digital data is indicative of an intensity value Ii(x,y) for each position (x,y) in each i-th spectral band. The intensity value for each position in each i-th spectral band is adjusted to generate an adjusted intensity value for each position in each i-th spectral band in accordance with ∑n=1N⁢Wn⁢(log⁢ ⁢Ii⁢(x,y)-log⁢ [Ii⁢(x,y)*Fn⁢(x,y)]),i=1,…⁢ ,Swhere Wn is a weighting factor, “*” is the convolution operator and S is the total number of unique spectral bands. For each n, the function Fn(x,y) is a unique surround function applied to each position (x,y) and N is the total number of unique surround functions. Each unique surround function is scaled to improve some aspect of the digital image, e.g., dynamic range compression, color constancy, and lightness rendition. The adjusted intensity value for each position in each i-th spectral band of the image is then filtered with a filter function to generate a filtered intensity value Ri(x,y). To prevent graying of white zones in the image, the maximum of the original intensity value Ii(x,y) and filtered intensity value Ri(x,y) is selected for display.

A display panel includes a light blocking pattern and a polarizer. The light blocking pattern is disposed on a base substrate. A plurality of opening areas is defined based on the light blocking pattern. The polarizer includes a plurality of linear patterns spaced apart from each other. The plurality of opening areas includes a color area transmitting color light and a white area transmitting white light. The polarizer overlaps the color area and the white area.

A projection unit is prepared for using light source module to provide an illumination light beam, setting both the first and the second colored wheels on light path of illumination light beam, arranging the first white color region and the second white color region separately on the first and the second colored wheels, setting area of the first white color region to be different from that of second one, electric-coupling control unit with the first and the second colored wheels. Its switching-over method of operation mode is also disclosed.

The invention discloses an automatic monitoring method for high-speed milling cutter abrasion, and belongs to the field of precision manufacturing. The method comprises the steps that an imaging device directly faces the end of a cutter to collect images repeatedly within the machining intervals set by a numerical control program, wherein the cutter is a milling cutter of a numerical control milling machine; gray-level mean square error counting is carried out on the middle area ( including the area where the cutter is located) of each acquired image, the image with the maximum mean square error is selected as a focused target image, and a white area formed by abrasion exists in the target image; and the abrasion parameter characteristics of the white area are extracted, wherein the abrasion parameters comprise a length, a width and an area, and the abrasion parameter characteristics are used as representation forms of cutter abrasion. According to the automatic monitoring method for the high-speed milling cutter abrasion, the abrasion amount of a micro-milling cutter can be monitored, and the service life of the cutter can be predicted; and damage to a to-be-machined semi-finishedworkpiece or reduction of machining precision caused by the over-damaged cutter can be avoided.

The invention discloses a high-precision multi-feature plane template. The high-precision multi-feature plane template includes a ChArUco black and white chequer template, wherein the chequer white area combination has an ArUco QR-code; the middle area of the ChArUco black and white chequer template is filled with random feature points to form a Random feature point template; and the edge area ofthe ChArUco black and white chequer template is provided with a plurality of segments with preset specific positions. The invention also provides a distortion optimization and calibration method of the high-precision multi-feature plane template. The high-precision multi-feature plane template and the distortion optimization and calibration method thereof have the advantages of solving the problemthat different focal length lens takes more images, consumes long operation time and is not accurate in edge distortion during the high precision calibration process; and conveniently and effectivelysolving the difficulty of calibration of a zoom lens by the calibration template, during the calibration process, having low requirement for the size of space, and not influencing the calibration function even when performing observation of part of the template; and the added linear segments around the calibration template, and being able to solve the problem of solving edge distortion without taking a large amount of images.

A system is disclosed for adjusting gain and offset values to set the best-fitted gain and offset values of R, G, and B video signals, by using stable area data of a video signal input to a liquid crystal display from a computer system during the production process of a liquid crystal display. First, the gain value is initialized to the maximum and the offset value to the minimum for adjusting the gain and offset values of the video signal input. Next, the offset value is adjusted by decreasing it until data of a video signal read by a base address register set for reading the stable area data of a black area is the same as the initialized minimum data. Finally, the gain value is adjusted by increasing it until data of a video signal read by the base address register set for reading stable area data of a white area is the same as the initialized maximum data.

A white balance correcting apparatus and a white balance correcting method are provided. A white balance correcting apparatus includes a white balance corrector configured to divide an input image into a plurality of blocks, determine, using a reference color temperature line, adjusted color temperatures of blocks included in a white area among the plurality of blocks, and calculate red (R) and blue (B) gains to which different weights are applied according to the adjusted color temperatures of the blocks.

The invention relates to an accurate positioning method for human eye on the basis of gray gradation information, belonging to the technical field of information. The method comprises: (1) human face detection: the area of a human face is positioned from an input image; (2) gray gradation column diagram analysis: gray gradation column diagram analysis is carried out on the human face image to determine the gray gradation range of the complexion area of the human face; (3) image strengthening: gray gradation adjustment is carried out on the image to enable eye characteristics to be more obvious; (4) Gabor wavelet filtration: Gabor wavelet filtration is carried out on the strengthened image, a real part image filtered by Gabor is synthesized to obtain a reference image; (5) cluster analysis: the synthesized reference image is analyzed by using the K-Means cluster method to obtain a binarization human eye candidate window, and the white area in each human eye candidate window after binarization is analyzed to determine the rough position of the human eye, so that the human eye window is obtained; (6) neighbourhood operation: the human eye window is scanned by two neighbourhood operators to determine the canter position of the pupilla. The invention has the advantages of simple detection method and accurate eye positioning.

Provided is a light source detection method and device. The method comprises that pixel points, which are positioned in a second area of a chroma space, of a detection image are determined, the second area corresponds to a first area of a standard graph card, and the first area is any one selected from a white area, a muted color area and a colorless area in the standard graph card; light-source color temperatures corresponding to different pixel points are determined on the basis of correspondence between pixel values of the pixel points and the light-source color temperatures as well as the pixel values of the pixel points in the second area; based on the light-source color temperatures corresponding to the pixel points in the second area, the pixel points are divided into pixel point sets corresponding to the light-source color temperatures; and the light-source color temperature of the detection image is determined according to the light-source color temperatures corresponding to the pixel point sets. The method can be used to accurately obtain the light-source color temperature, processing including automatic white balance can be implemented on the image according to the obtained light-source color imaged of the detection image, the color completeness of the image is effectively ensured, and the image processing quality is improved.

The invention provides a multi-feature nighttime vehicle detection method based on machine vision. The method comprises the steps that an upper boundary line and a lower boundary line are delimited on a detected image to obtain an area needing to be detected; in the detecting area, the binary images of a red area and a white area are obtained through the color and the brightness feature of a nighttime vehicle taillight; according to the space features of the nighttime vehicle taillight, searching is conducted on the binary images of the red area and the white area to obtain candidate taillight images; then the candidate taillight images are searched for to obtain the specific information of candidate taillights; at last, the candidate taillights are matched according to the geometric feature rules of vehicle taillight pairs so that the candidate taillight pairs can be obtained. The multi-feature nighttime vehicle detection method based on machine vision is suitable for a vehicle-mounted road target detection system based on vision, and the real-time performance and the interference resistance of the target detection system are improved. The multi-feature nighttime vehicle detection method based on machine vision is suitable for the field of vehicle intelligent anti-collision early warning and the technical field of vehicle detection.

The invention relates to a seedling walnut bark tongue access grafting method, which comprises the following steps that prepared walnut scions are cut into horse ear shapes, and in addition, the lower ends are pinched open by hand, so that the xylem part is separated from the bark; the main stem smooth part is subjected to stem cutting, and old bars are cut away; the lower end xylem parts of the prepared scions are inserted under the barks of stocks, two full buds are reserved at the upper ends, and the lower end bark layers of the scions are combined with the new bark layers of the stocks subjected to the old bark removal; white areas are exposed around the scions so that the wounds can be heeled and the callus tissues can be formed; the wounds are tightly covered by mulching films, and then, the scions are fixed by plastic bags. After the stocks and the scions are fixed, the plastic bags sheath the scions from the upper ends to positions under the connectors, and the openings of the plastic bags are tightly tied for moisture preservation. A paper roll rolled by newspaper sheaths the outside of the plastic bags for shading sun-proof protection, the lower end is tied in, and the upper end is folded down. When the method provided by the invention is adopted, the walnut trees bear fruit 5 to 7 years earlier than the walnut trees cultured in a seedling way, the quality is good, the stable transfer of high quality and good variety features is ensured, and the problem of great lateral generation separation of seedlings can also be solved.

The invention relates to a uniform light source illumination adjustable color filter optical spectrometer, which is characterized in that: a uniform light source illumination structure is adopted in an optical system, and a color filter array is switched by a mechanical switching device; the whole device comprises a uniform light source structure 3, the color filter array 4, the mechanical switching device, a black-white area array CCD6, a data acquisition processing system and the like; a power supply scheme of a constant-current source 2 is adopted, and an integrating sphere is used as the uniform light source structure; the color filter array 4 adopts a mode of combining a width band with a narrow band; and the color filter array 4 is switched quickly by adopting a step motor driving mode. The uniform light source illumination adjustable color filter optical spectrometer has the characteristics of high resolution, wide spectral range, high light flux and structure miniaturization, and is particularly suitable for multi-spectral imaging systems in the fields of static target recognition and component analysis.

The invention discloses a human face eye area image enhancement method and system and a shooting terminal. The method is characterized by, carrying out eye area feature point identification on an image to be processed to obtain an eye area; dividing the eye area into an eye pupil area and an eye white area; then, carrying out brightness enhancing processing on the eye pupil area and carrying out whiteness enhancing processing on the eye white area to obtain a brightness-enhanced eye pupil area and a brightness-enhanced eye white area respectively; and carrying out transition processing on the boundary between the eye pupil area and the eye white area to obtain a result image. Therefore, layering feeling of the eye area in the human face image can be enhanced effectively; the problems that adjustment effect is not obvious and natural, eye area layer cannot be restored and applicability is not high and the like in a conventional eye area enhancement algorithm are improved, and the effect of enhancing and beautifying the eye area in the human face image is achieved; the method is simple in algorithm, fast in operating speed and wide in application range; and the human face image eye area image enhancement effect is obvious and natural.