558 results about "Color model" patented technology

A system and method are provided for tracking a face moving through multiple frames of a video sequence. A predicted position of a face in a video frame is obtained. Similarity matching for both a color model and an edge model are performed to derive correlation values for each about the predicted position. The correlation values are then combined to determine a best position and scale match to track a face in the video.

Segmentation of foreground from background layers in an image may be provided by a segmentation process which may be based on one or more factors including motion, color, contrast, and the like. Color, motion, and optionally contrast information may be probabilistically fused to infer foreground and / or background layers accurately and efficiently. A likelihood of motion vs. non-motion may be automatically learned from training data and then fused with a contrast-sensitive color model. Segmentation may then be solved efficiently by an optimization algorithm such as a graph cut.

A method, system, and computer-readable storage medium for automatic segmentation of a video sequence. A segmentation shape prediction and a segmentation color model are determined for a current image of a video sequence based on existing segmentation information for at least one previous image of the video sequence. A segmentation of the current image is automatically generated based on a weighted combination of the segmentation shape prediction and the segmentation color model. The segmentation of the current image is stored in a memory medium.

A method of forming at least one three dimensional (3D) color image of at least one object in a target space. The method comprises projecting, each of a plurality of projection cycles, a sequence comprising a plurality of gray coded light patterns, each colored in one of red green or blue, on a target space, capturing a plurality of two dimensional (2D) images of the target space during a plurality of acquisition cycles, each the acquisition cycle being timed to correspond with the projection of at least a sub sequence of the sequence, the sub sequence comprising red, green, and blue gray coded light patterns of the plurality of gray coded light patterns, extracting range data and color texture information of at least one object in the target space from the plurality of 2D images, and forming a 3D color image of the range data and color texture information.

An image processing method includes photographing an object by a camera via a filter, separating image data, which is obtained by photographing by the camera, into a red component, a green component and a blue component, determining a relationship of correspondency between pixels in the red component, the green component and the blue component, with reference to departure of pixel values in the red component, the green component and the blue component from a linear color model in a three-dimensional color space, and finding a depth of each of the pixels in the image data in accordance with positional displacement amounts of the corresponding pixels of the red component, the green component and the blue component. The image processing method further includes processing the image data in accordance with the depth.

The invention relates to a removing method for a glasses frame in a face image. The method comprises the steps of: detecting and positioning eyes in the input face image with a pair of glasses, geometrically correcting the face image on the basis of the positioned result to form a first image; extracting an eye estimation area from the first image to obtain a second image, and conducting mathematical morphology processing on the second image so as to determine the position of a glasses frame; based on the first image, establishing a face skin color model; in the second image, interpolating each pixel point of the glasses frame the position of which is determined, correcting the interpolation result in a part of pixel points of the glasses frame according to the skin color model, and conducting de-noising processing to form a ninth image; and replacing the eye estimation area in the first image by the ninth image, synthesizing and outputting the face image the glasses frame of which is removed. According to the technical scheme, the glasses frame in the face image with a pair of glasses can be conveniently and effectively removed, and the face recognition rate can be further improved.

Methods, apparatuses and systems for tooth shade analysis and matching are disclosed. A method embodiment according to the invention includes acquiring at least one image, the image including one or more teeth of a patient and normalization references, normalizing the at least one image in accordance with the normalization references, determining the color of the teeth as composed of colors from one or more selected shade standards, communicating the standardized color information to a dental laboratory, manufacturing a dental prosthesis based on the standardized color information and installing the dental prosthetic. Normalization is performed to correct patient images for variations in lighting conditions and image source. Normalization references include a black reference, a white reference and at least one color reference. The normalized image is standardized by matching the pixels of the normalized image to selected shade standards. Selected shade standards may include incisal tooth shade standards. The standardized color image and / or analysis may be communicated to a dental laboratory according to aspects of the invention. The dental prosthesis can then be manufactured by a lab technician by referring to the standardized image. Color models according to the invention may include RGB, HSI and other models for representing color images. The methods, apparatuses and systems for tooth shade analysis and matching are also applicable to direct restorations of natural teeth, such as repair of chipped or broken teeth.

Fire detection and smoke detection use an image capturing device to obtain images from a predetermined area and adopts an RGB (red, green, blue) color model based chromatic and disorder measurement for extracting fire pixels and smoke pixels. The extracted pixels are inputted to a fire detection fuzzy alarm system to generate an output of alarm information. Based on iterative checking on the growing ratio of the alarm information, a fire alarm is released accordingly.

A method, system, and computer-readable storage medium for applying Gaussian Mixture Models (GMMs) to local image patches using an adaptive color lookup table. Per-channel color quantization may be performed to find representative colors for a local image patch. Each combination of the representative values corresponds to a representative color. The probabilities of the representative colors may be computed using a local GMM color model and stored to corresponding entries in an adaptive color lookup table. For every pixel in an image patch, the closest representative color may be found, and the corresponding probability may be retrieved from the lookup table and used for the pixel. The method may, for example, be applied to each local window in a method for automatically determining segmentation in a digital video image sequence to calculate the foreground probabilities for the pixels in a propagated classifier via a GMM.

The present invention is embodied in a system and process for automatically learning a reliable color-based tracking system. The tracking system is learned by using information produced by an initial object model in combination with an initial tracking function to probabilistically determine the configuration of one or more target objects in a temporal sequence of images, and a data acquisition function for gathering observations relating to color in each image. The observations gathered by the data acquisition function include information that is relevant to parameters desired for a final color-based object model. A learning function then uses probabilistic methods to determine conditional probabilistic relationships between the observations and probabilistic target configuration information to learn a color-based object model automatically tailored to specific target objects. The learned object model is then used in combination with the final tracking function to probabilistically locate and track specific target objects in one or more sequential images.

The invention discloses a method for identifying flame by video, a method for monitoring fire, and a system thereof. The method for monitoring fire comprises the following steps: acquiring video image, establishing a background model, and detecting prospect target in the video image; transmitting the image of the prospect target to a server end; judging which target points of the prospect target are color points of flame according to the color model of the flame established by training image; carrying out cluster analysis on the color points of the flame of the prospect target to acquire a flame area of the prospect target, and matching the prospect targets of the front and rear frame images; judging whether flame occurs in the flame area; when the matching relation exceeds the set threshold value; carrying out verification of a alarming verification mechanism when judging that flame occurs in the flame area; and when satisfying the warning condition, performing warning. The inventionhas wider range of application without limiting distance of scene, and achieves intelligentized processing.

The invention proposes an indoor fire and flame detection method based on high-definition video images. Firstly, a background image is established and updated in video monitoring images; sample picture elements are trained by a Fisher classifier so that a color model of flames is acquired; a foreground moving image is acquired through a background differencing method; flame suspected pixels are detected through color features of the fire flames, that is, pixel points (that is, suspected flame pixel points) with the color features of the flames are found in the foreground moving image and all of the suspected flame pixel points form a flame area; pixel connection areas are combined so that an external rectangle of the suspected flame area is acquired; circularity of the connection areas in the external rectangle is calculated according to morphological characteristics of the flames and a suspected flame area is judged according to the circularity, jitter analysis and flame continuity analysis and the like in the external rectangle; and if preset requirements are met, the suspected flame area is a real flame area and an alarm signal is sent out.

A flame detecting method is provided. The method comprises steps of capturing a video segment for a object; analyzing if an image of the object is moving; analyzing at least one of a color model and a flickering frequency of the moving object; comparing analyzed results obtained from the analyzing steps to a flame feature; and determining if the object is a flame.

The invention discloses a screen background setting method and a movable terminal. The screen background setting method comprises the following steps: when the icon of the movable terminal on a current screen is changed, the movable terminal builds up a color model according to the changed icon; the movable terminal calculates the color difference between the background of the current screen and the changed icon according to a color model of the background of the current screen and the color model of the changed icon; and the movable terminal judges whether the background of the current screen needs to be changed according to the color difference between the background of the current screen and the changed icon, and when the judgment is yes, the movable terminal replaces the background of the current screen according to a color model of a target screen background and the color model of each icon.

The invention relates to a method for fire identification through infrared and visible-light video image fusion. A fire is identified through an infrared image preprocessing module, a suspicious infrared image judging module, an infrared image flame determining module, and a visible light fusion comprehensive judgment module. The infrared image preprocessing module is used for carrying out graying treatment, region connection, binarization and dilation operation on an image. The suspicious infrared image judging module is used for calculating the difference between the gray-scale map and the binary image to determine a suspicious image of which the scene changes. The infrared image flame determining module is used for calculating the similarity between two sequential frames of suspicious image to determine whether there is flame. The visible light fusion comprehensive judgment module is used for judging whether the RGB value of a corresponding visible-light image meets a color model of flame based on the model of the flame in an RGB color space and finally judging whether there is a fire. Fusion identification of infrared and visible-light images is realized, missing and false fire reporting is avoided, and the accuracy of fire identification is improved.

Embodiments described herein are directed to generating physical three-dimensional color-accurate objects based on a 3D computer-based color model using printed layers of media. Embodiments can slice a 3D computer-based color model into 3D cross-sectional components, which retain the color information of the model. The 3D cross-sectional segments can be converted into 2D page images and the color information can be included in a plan image corresponding to the cross-sectional segments. Embodiments can print the page images to form cross-sectional prints which can be layered and trimmed to shape the prints into a color accurate physical object that represents the model.

A method capable of determining fingerprint authenticity is disclosed. The method includes capturing a fingerprint image, performing an analysis program when executed analyzing the fingerprint image using a first color model to obtain a first chromaticity coordinate corresponding to the fingerprint image, performing a conversion program when executed converting the first chromaticity coordinate into a second chromaticity coordinate, performing a verification program when executed determining whether the second chromaticity coordinate satisfies a second predetermined skin color threshold, when the second chromaticity coordinate satisfies the second predetermined skin color threshold confirming the fingerprint image is authentic, and concluding the fingerprint image is forged when the second chromaticity coordinate fails to satisfy the second predetermined skin color threshold.

The invention provides an ink fountain roller, an ink distributing unit and an ink distributing system of a carving photogravure press. The ink duct roller is a cavity-die inking roller with quasi-grains at the surface, and the quasi-grains correspond to forme grains; the ink distributing unit comprises an ink fountain, the ink fountain roller, a hook type scraper and an elastic color model roller, wherein the ink fountain roller contacts with ink in the ink fountain, the scraper is arranged at one side of the ink fountain roller, the elastic color model roller is arranged at the other side of the ink fountain roller and is in rolling transmission with the ink fountain roller; and the ink distributing system also comprises a gravure roller and an impression roller. The ink fountain roller of the ink distributing unit transmits ink grains which correspond to the gravure grains and have different thicknesses to the color model roller to form basso-relievo-shaped quasi-grain ink; the basso-relievo-shaped quasi-grain ink is transmitted into the gravure grains on the gravure roller; and the gravure roller and the impression roller mutually press to carry out printing. The invention has short ink path, easily ensures the accuracy of ink distribution and easily maintains the printing adaptability without ineffective circulation for the ink.

The present invention provides a method for simultaneous hue phase-shifting and a system for 3-D surface profilometry, wherein a single structured-light fringe pattern with encoded multiple trapezoidal color fringes is projected on an object so as to obtain a color image having deformed fringe patterns and then a hue information extracted from a HSI color model associated with the fringe pattern is transformed into a hue phase-shifting information for restructuring the 3-D surface profile of the object. Since the color structured light is composed of a plurality of colorful light having phase shifts with each other in spatial domain, the single structured-light pattern comprises multiple hue phase-shifting information so that the phase shifting and unwrapping can be performed by one-shot 3-D surface reconstruction process without needs of traditional conventional phase wrapping and Euler's transformation procedures such that the efficiency of phase shifting and 3-D surface measurement can be improved.

The invention provides a target person hand gesture interaction method based on a monocular video sequence. The target person hand gesture interaction method comprises the following steps: first, acquiring an image in a monocular video frame sequence, using a movement detection algorithm to extract a movement foreground mask, and using a palm classifier to detect the minimum circumscribed rectangle frame of a palm and screen the palm of a target person; extracting a color histogram model from the palm image of the target person, calculating the reverse projection drawing of the palm image of the target person, and summarizing the area model of the palm of the target person; for a tracked target region, using a color model to calculate the reverse projection drawing, and calculating the area of the current frame of a target person hand to judge the static gesture of the target person hand: a fist or the palm; using the fist gesture or the palm gesture to carry out click or move interaction control. The target person hand can be screened under complicated background, and the tracking of any hand gesture and the recognition of any preset trajectory are finished. The method can be applied on an embedded platform with low operation capability and is simple, speedy and stable.

The invention relates to a winter jujube disease identification method based on a deep convolutional neural network and a disease image. The method includes the following steps that: an original winter jujube diseased fruit RGB color image collected by an Internet of Things is converted into a YUV color model, and preprocessing is performed; the a rectangular region of interest of disease spots which contains a disease image is extracted, the rectangular region of interest is segmented through using a K-means clustering algorithm, so that a YUV color disease spot image can be obtained; and a three-channel layered convolutional neural network model is constructed and is trained by using training data, and a jujube disease image to be recognized is inputted into the trained model so as to be subjected to disease category identification. The method of the invention can be applied to an Internet of Things-based greenhouse winter jujube disease monitoring system and can obtain accurate disease identification results.

The invention discloses an automatic fast segmenting method of a tumor pathological image. The method comprises the following steps: firstly filtering a tumor original pathological image through the adoption of a Gaussian pyramid algorithm to respectively obtain pathological images with equal resolution, double resolution, fourfold resolution, eightfold resolution and 16-fold resolution; determining an initial region of interest containing the tumor on the equal resolution image through a RGB color model and morphological close operation; iteratively optimizing the initial regions of interest from the equal resolution to the fourfold resolution through the adoption of bhattacharyya distance; judging that the contribution of the RGB color model to the tumor region of interest has been reduced to zero when the bhattacharyya distance achieves a set threshold value; performing the self-adaptive high resolution selection of the deep precise segmentation through the adoption of a convergence exponent filtering algorithm, thereby further segmenting under the most suitable high resolution; and finally segmenting out a normal tissue and a tumor tissue in the tumor region of interest through the adoption of a bag of words model based on random projection. The method disclosed by the invention has the features of being accurate, fast and automatic.

A method of classifying images based on elliptical color models is utilized in a number of applications. One or more color models are generated from a set of images with a region of interest. Then, sets of images are utilized for training. One set of images has regions of interest, and the other set of images is without regions of interest. By utilizing the two sets of images, a maximum difference between the sets is achieved, so that a color model is most representative of the object desired. Then using the optimal color model, a collection of images are able to be searched, and images are retrieved based on the probability that the images contain the desired object.

The invention relates to a method for monitoring a moving object in a natural environment. Based on space-time information fusion and feature identification, the method mainly comprises background analysis, foreground extraction, shadow removal and background update. According to the thought of the method, image sequences are converted into hue, saturation and value (HSV) color models, the change rule of the parameter of each pixel point in a certain period of time is analyzed and compared, and each pixel point belonging to a background point, a moving object point or a shadow point in a certain frame can be distinguished through judgment of a judgment formula. By adopting the method, an algorithm is improved on the influence possibly caused by natural conditions such as wind, sunlight and lightning, and the background can be intelligently updated under the conditions that the illumination is abruptly changed, the moving object is still and then is blended into the background, the background object moves and the like; and the method is applied to monitoring of the moving object in the natural environment.

A new color model HMMD is disclosed based upon hue, the shade, the tone, the tint and the brightness of a color, and a color quantizing method using the HMMD color space. The present invention regards the colors adjacent to a given color in the color space as the neighboring colors to consider indices of the neighboring colors as the partial values according to the distance. Accordingly, the present invention can accomplish a color quantization close to the change of the color sensed by the human eye, thereby capable of enhancing a performance of the image searching system based on content.< / PTEXT>

The invention discloses a video smog fine classification method based on a color model and motion characteristics, comprising steps of differentiating and constructing a color model on the basis of a gauss mixing model and a background, detecting a motion pixel point and performing initial screening, obtaining a motion object connected region, extracting a motion changing characteristic, setting a threshold and determining whether a suspicious smoke area exists, performing pre-processing on the suspicious smoke area, extracting a SIFT characteristic on the basis of an image block, combining with an SVM optimization random forest algorithm, performing training based on the suspicious smoke area image block and thus realizing the fine classification of the fire hazard smoke, the cigarette smoke, the water vapor, etc. The video smog fine classification method based on color model and motion characteristics performs video smoke detection based on the color model and the motion characteristic and by targeting the fine classification, realizes real-time fast smoke detection, effectively eliminates the interference having similar effect interference sources with the fire hazard smoke, and improves the detection efficiency and accuracy.

Three or more materials are advantageously separated from dual energy data by using a material separation technique. To effectively separate material clusters, a density plot is introduced to automatically render cluster separations. Initially, the projection data optionally undergo data-domain dual energy decomposition. Then, the image data is plotted in a vector plot whose axes are the low HU values and the high HU values. For a given data point in the vector plot, a number of data points is counted within in a region of interest surrounding the given data point to generate a density plot where each point now represents a density level surrounding the data point. Thus, clustering of a certain material is visualized by a predetermined color assignment scheme. Furthermore, special image processing methods such as Gaussian decomposition are used to improve the accuracy of material separation. In addition, the HSL color model may be used for better visualization and to bring a new dimension in material separation display.

An apparatus and method for obtaining a data file representing a natural color three-dimensional image of the surface of a subject are disclosed. The apparatus incorporates a plurality of scanners, each comprising illuminating means and digital camera means, disposed about the subject, and computer means to correlate the images and store the data file. An apparatus and method for producing a natural color three-dimensional model from that data file are also disclosed. The use of rapid prototyping and manufacturing technology for manufacturing a model is disclosed. The present invention is particularly applicable to human subjects.

The invention discloses a method and a system for sorting defective contents of a digital video. The method comprises the following steps: firstly establishing a blood color model and a skin color model, and initializing a threshold value; then carrying out defective video feature detection on video images, and sorting defective video features, wherein the defective video feature detection comprises motion detection, character detection, sensitive position detection, skin color pixel detection and blood color pixel detection; and then determining the restricted grade of the video images comprehensively according to the detection sorting result of the detecting and sorting steps. By virtue of introducing the skin color pixel detection and the blood color pixel detection, the detection rate and the reliability are improved, and obtained proportion features become more reliable, thus the detection rate of the detected defective video can be improved accurately, and the control service of a multimedia video and the automatic grading of a movie video are convenient.