852 results about "Region of background" patented technology

A method for generating an enhanced compressed digital image, including the steps of: capturing a digital image; generating additional information relating to the importance of photographed subject and corresponding background regions of the digital image; compressing the digital image to form a compressed digital image; associating the additional information with the compressed digital image to generate the enhanced compressed digital image; and storing the enhanced compressed digital image in a data storage device.

A system for automatic counting of non-overlapping objects irrespective of shape, size, and color is provided by imaging and computer subsystems. Objects to be counted are placed on a transparent surface disposed on a diffusing surface uniformly irradiated by electromagnetic radiation sources. Low intensity object shadows and high intensity object background regions are digitally imaged. The digital image is converted by a computing unit to a binary image and subjected to the Distance Transform to determine a count of the objects. Object identification verification is provided by comparing identification information obtained from a bar code associated with a supply container of the objects and identification information obtained from a digitally imaged written request.

The invention relates to an intelligent assisted driving method and system. A lane line is obtained as follows: an image, shot by a camera, of a road in a vehicle driving direction is obtained; de-distortion processing is carried out on a video frame of the image by using an internal reference matrix of the camera and inverse perspective transformation is carried out on a selected to-be-transformed region src of the video frame; threshold segmentation is carried out on the video frame after inverse perspective transformation and a lane line and a background region are separated; statistics iscarried out on the lower part of the image after threshold segmentation and an intersection point of the lane line and the bottom of the image is obtained by statistics; searching is carried out by starting with the intersection point by using a sliding window, m pixels corresponding to the lane line are determined, and curve equation fitting is carried out on the m pixels to obtain a fitted laneline. With the method and system provided by the invention, the lane line is displayed in a display device inside the vehicle; and various conditions like sudden illumination changing, tree shadow shielding, and pavement blotting are detected accurately. The method and system have advantages of high applicability, low cost, high precision, good real-time performance and high stability.

The invention discloses an identification method and system of lateral deviation of a vehicle driving route. According to the method and system, firstly, an image, which is shot by a camera mounted ona vehicle, of a road along a vehicle running direction is acquired; an internal-parameter matrix of the camera is utilized to carry out de-distortion processing on the video frame, and inverse perspective transformation is carried out on a selected to-be-transformed region src; then threshold segmentation is carried out on the video frame to separate lane lines from a background region; then locations where maximum values appear are derived by counting to use the same as intersection points of the lane lines and the bottom of the image; and whether correction of lateral deviation of the driving route needs to be carried out is judged according to separation distances between the locations of the intersection points and a preset lateral mounting location of the camera on the vehicle. In acase where the vehicle deviates from a road center too far, the method and system can know the case in time, and remind a driver or carry out correction; and the method and system can accurately detect all of sudden illumination changes, tree shade shading, road surface stains and many other conditions, and are high in applicability, low in costs, high in precision and better in real-time performance and stability.

A harmonization system and method are disclosed which allow harmonization of a set of digital images. The images are automatically segmented into foreground and background regions and the foreground and background regions are separately harmonized. This allows region-appropriate harmonization techniques to be applied. The segmenting and harmonizing may be category dependent, allowing object-specific techniques to be applied.

The sharpness of a digital image is adjusted according to defined aim subject and background sharpness levels. An image segmentation process is used to segment an input digital image into a subject region and a background region. The subject and background regions are analyzed to determine corresponding subject and background sharpness levels. An enhanced digital image is formed wherein the sharpness of the subject region is adjusted responsive to the subject sharpness level and the aim subject sharpness level, and the sharpness of the background region is adjusted responsive to the background sharpness level and the aim background sharpness level. In some embodiments, the input digital image is analyzed to determined a scene type classification and the aim subject and background sharpness levels are defined in accordance with the determined scene type classification.

An algorithm for estimating which pixels belong to the background of a scanned page. The algorithm is particularly designed to handle situations in which the page background varies in color / intensity, as is case when bleed-through artifacts from the reverse side of the page appear in the background. In determining background regions, including properly classifying bleed-through artifacts regions as such, the algorithm uses multiple local and global criteria for making the determination. In addition to being able to find large connected pieces of background, the algorithm is also able to find isolated islands of background by analyzing transition characteristics of neighboring regions. Regions are identified on the basis of similar local features and also by the nature of transitions between foreground regions that do not directly share a boundary. An adaptive white-point adjustment technique based on identified background regions improves the perceived quality of the printed output.

A blur classification module may compute the probability that a given pixel in a digital image was blurred using a given two-dimensional blur kernel, and may store the computed probability in a blur classification probability matrix that stores probability values for all combinations of image pixels and the blur kernels in a set of likely blur kernels. Computing these probabilities may include computing a frequency power spectrum for windows into the digital image and / or for the likely blur kernels. The blur classification module may generate a coherent mapping between pixels of the digital image and respective blur states, or may perform a segmentation of the image into blurry and sharp regions, dependent on values stored in the matrix. Input image data may be pre-processed. Blur classification results may be employed in image editing operations to automatically target image subjects or background regions, or to estimate the depth of image elements.

An image processing apparatus may detect an occlusion boundary between objects within an input depth image by applying an edge detection algorithm to the input depth image. The image processing apparatus may classify the occlusion boundary into a foreground region boundary and a background region boundary using a depth gradient vector direction of the occlusion boundary, and may extract an occlusion region of the input depth image using the foreground region boundary.

A technique involves distinguishing between foreground and background regions of a digital image of a scene. First and second images are captured of nominally a same scene. The first image is a relatively high resolution image taken with the foreground more in focus than the background, while the second image is a relatively low resolution reference image taken with the background more in focus than the foreground. Regions of the captured images are assigned as foreground or background. In accordance with the assigning, one or more processed images are rendered based on the first image or the second image, or both.

An aerial photography transport video vehicle rapid detection method comprises the steps that: step 100, the space-based coding part adopts the global motion estimation to determine the global motion vector of a background; step 200, the residual difference value is calculated according to the global motion vector to divide background regions and motion regions; step 300, whether the regions are the background regions or not is judged, an image of which the regions are all the background regions is changed to the next frame, and the step 200 is executed; otherwise, the motion regions of the image execute the step 400; step 400, the ground part firstly determines a self-adaptive gradient threshold which is lower and can correctly divide various objects to carry out the primary marker extraction; then two parameters of an area and a water collection depth are introduced for further screening of the extracted marker, thus determining a final marker point; then the marker point is taken as the region minimum value for carrying out the VS watershed division; finally, the regions are merged according to the texture information of the regions; step 500, the shadow is detected in an HSV color space, thus filtering out phony targets and finally detecting vehicles. The method of the invention solves the problems that the calculation amount during the decompression of the aerial photography image and the detection of motion targets is greater, and the real-time property and the robustness requirement are difficult to be satisfied at the same time.

The invention discloses a scene text recognition method based on sparse coding characteristics, and relates to computer vision and pattern recognition. The method includes the steps: inputting a natural scene text image to be recognized; by the aid of a multi-scale sliding window method, detecting and recognizing a window area in the image by a character classifier, for each character class, determining a large output area of the classifier as a candidate character area, determining a small output area as a background area, finding the candidate character area in the image, retaining the area with the largest output value of the classifier and the corresponding character class for the area with a large overlapping ratio by the aid of a non-maximum suppression method, and removing the repetitive and redundant candidate character area to obtain a character detection result; combining detected characters into a word or text line; outputting a scene text recognition result. Structural characteristics of the characters can be more effectively expressed and extracted, so that the recognition rate of a scene text is increased.

A method of recognizing a document image including a plurality of areas is provided. The method includes the steps of inputting the document image as a digital image, specifying a background color of the document image, reducing the size of the document image if necessary, extracting a plurality of pixels located in areas other than a background area from the document image by use of the background color, creating a plurality of connected elements by combining the plurality of pixels, and classifying the plurality of connected elements into a plurality of fixed types of areas by using at least features of shapes of the plurality of connected elements to obtain an area-separated document image. Additionally, a feedback process is performed if necessary, by performing binary area separation to a binary image and comparing a result of the binary area separation and a result of color area separation, to create a binary image suitable for an OCR process and to obtain a result of area separation.

The invention discloses a tobacco leaf grading method based on reflection, perspective and microscopic images. The method provided by the invention comprises the following steps: (1) acquiring a high-definition color reflection image, a high-definition perspective image and a high-definition microscopic image of tobacco leaf at real time and transmitting the collected images to an industrial control computer; (2) preprocessing the images to quickly position the edge of tobacco leaf and segmenting tobacco leaf out of a background area to record as a tobacco image; (3) extracting features of the image, wherein the features include shape feature, color feature and texture feature; and (4) analyzing the above features of tobacco leaf by an Adaboost sorting algorithm, and determining the grade of tobacco leaf through part, color and grade classification of tobacco leaf. Through a device for full-automatic machine grading, human factor interference can be avoided, and labor cost is greatly reduced. Thus, huge hidden costs of training, management and the like caused by manual grading are completely avoided.

The invention discloses a corrugated board production quality regulation and control method based on machine vision, relates to the field of artificial intelligence, and is mainly used for mechanical parameter control of corrugated board production. The method comprises the steps of obtaining a target surface grayscale image; obtaining the gray gradient direction of each pixel point; calculating the defect probability of each pixel point; establishing a gray level histogram, calculating a background probability value of each gray level, and obtaining a background region of the gray level image; calculating the abnormal degree of each pixel point in the grayscale image, and constructing a sequence of all abnormal degrees in the grayscale image; calculating an influence degree value of each abnormal degree sequence to obtain an overall influence degree value of the target surface image; and adjusting production machinery parameters according to the overall influence degree value of the target image. According to the technical means provided by the invention, the influence degree of the defect is calculated through the target surface grayscale image, so that the mechanical parameters are adjusted, and the product quality and the production efficiency are improved.

The present invention provides a technique of accurately extracting areas of characters included in a captured image. A character extracting device of the present invention extracts each character in an image with compensated pixel values. In more detail, the character extracting device integrates pixel values at each coordinate position in the image along a character extracting direction. Then, the character extracting device predicts the background area in the image based on the integrated pixel value. The compensated pixel values are compensated based on integrated pixel values at the predicted background area from integrated pixel values at each coordinate position.

A variable data pantograph is formed by receiving a variable data string and retrieving at least one character representation from a vocabulary of character representations stored in memory. The retrieved at least one character representation corresponds to the variable data string. Each of the character representations in the vocabulary is associated with a foreground region including a character shape and a background region suitably sized and arranged for encompassing the foreground region. The background region incorporates a first pattern of elements and is controlled to render a target color using a first set of color separation control data and the foreground region incorporates a second pattern of elements and is controlled to render the target color using a second set of color separation control data. The retrieved at least one character representation is assembled to form a variable data pantograph, whereby when the variable data pantograph is rendered in an original document, the foreground and background regions are similar in tone, the foreground and background regions being substantially less similar in tone in a copy of the original document to render the character visible.

An image pickup apparatus detects a face region out of an image signal representative of a field picked up by an image pickup device, and compares the lightness of the face region or a person region with the lightness of a background region also included in the image signal to thereby determine whether or not a subject is backlit. The apparatus causes, if the subject is backlit, the image pickup apparatus to execute actual pickup with backlight correction.

A segmentation of an object depicted in a first visual representation may be determined. The segmentation may include for each image a first respective image portion that includes the object, a second respective image portion that includes a respective ground area located beneath the object, and a third respective image portion that includes a background area located above the second respective portion and behind the object. A second visual representation may be constructed that includes the first respective image portion and a target background image portion that replaces the third respective image portion and that is selected from a target background image based on an area of the third respective image portion relative to the respective image.

The invention relates to a kilowatt-hour meter image automatic identification method which comprises the following steps: 1. image preprocessing: detecting vertical texture of a panel image by using Sobel operator, preliminarily removing the background area by a projection method, extracting the area with abundant vertical texture by an expansion method, and carrying out binarization treatment on the image by a adaptive threshold segmentation method based on an integral projection method; 2. precise positioning of indicating value and bar code: by combining an intelligent judgment method on the basis of indicating value intervals and length-width ratio characteristic of numeric characters under the complex image background, adapting to precise positioning of indicating values of different types of kilowatt-hour meters on the basis of vertical edge detection of the Sobel operator and morphological treatment; carrying out horizontal scanning on the bar code area to extract the bar code characteristic area; 3. bar code identification: identifying different character bar codes by using a similar edge distance normalization method; and 4. indicating value identification: extracting the indicating value by a PCA (principal component analysis) method. By using the PCA character recognition method, various character indicating values can be precisely identified, including identification of half-character.

A harmonization system and method are disclosed which allow harmonization of a set of digital images. The images are automatically segmented into foreground and background regions and the foreground and background regions are separately harmonized. This allows region-appropriate harmonization techniques to be applied. The segmenting and harmonizing may be category dependent, allowing object-specific techniques to be applied.

An image preview method, apparatus, and terminal are disclosed to provide a technical solution in which a background blurring effect with respect to a current scene can be previewed in real time. A terminal device synchronously obtains preview images of a current scene from different angles in a dual-camera photographing preview mode by using a dual-camera module, calculates, in the preview images based on a phase difference generated by a distance and an angle of the dual-camera module, a depth of field of each pixel unit included in a preview image, obtains a foreground depth of field of a preset target area in the preview image, and determines, in the same preview image, an area including all pixel units having a depth of field beyond a range as a background area. The terminal device also performs blurring processing on the background area by using a preset blur coefficient, and outputs an image including the target area and a blurring-processed background area as a real-time preview image of the current scene.

A technique involves distinguishing between foreground and background regions of a digital image of a scene. First and second images are captured of nominally a same scene. The first image is a relatively high resolution image taken with the foreground more in focus than the background, while the second image is a relatively low resolution reference image taken with the background more in focus than the foreground. Regions of the captured images are assigned as foreground or background. In accordance with the assigning, one or more processed images are rendered based on the first image or the second image, or both.

When one viewing condition parameter is applied to all pixels, a visual effect between a single color and a background expressed on a rasterized image cannot be reflected on a color matching result. To prevent this, when color matching using a human color appearance model is to be performed, the distance between an image and a viewer and the resolution of the image are input. On the basis of the input distance and resolution, a stimulus region, adjacent region, and background region based on a plurality of field angles (e.g., 2°, 4°, and 10°) for a pixel of interest on the image are defined, thereby determining a viewing condition parameter and performing color matching.

The invention provides an image coding method which is applied to the field of computer image processing. The method comprises the following steps of: firstly, marking the region of interest in an image; performing wavelet transform of the original image; finding the wavelet coefficient corresponding to the pixel of the region of interest after the transform in a wavelet coefficient matrix; then,quantizing the background region and the region of interest according to different quantizing standards so that the coefficient of the region of interest is located in a higher plane; performing threshold quantization of the wavelet coefficient matrix nearby; and coding by a method based on SPIHT (set partitioning in hierarchical trees). The method provided by the invention guarantees the high compression ratio as well as the display quality of the region of interest of a user; and when transmitting or browsing an image in a wireless network with a relatively low rate, the method can enable the user to get the most important information in the image very soon.

The invention discloses a cutting-resistant JPEG image compression history and synthetic tamper detection method. The method comprises the following steps: (1) calculating compression history trace and cutting position of an image to be detected; (2) determining whether the image to be detected has a tampered operation or not; (3) carrying out tamper area positioning on the image determined in the step (2), respectively figuring out difference images to RGB image three channels according to the mode of the step (2), carrying out binary processing on the difference images, carrying out logic and operation on the obtained three channel binary images to obtain a new binary image, carrying out morphological corrosion expansion operation on the image, and mapping back to the image to be measured to obtain a tampered area positioning image. According to the invention, problem is solved that block position of a JPEG image may be destroyed after cutting, which leads to sectional or complete failure of the prior art. Also effective detection and tampered area positioning on an image with cutting background area can be carried out by the method provided in the invention.

The invention discloses a printed matter defect detection method and device based on artifact elimination. The method comprises steps of image positioning and registration, carrying out the positioning and registration of a standard template image and a target image of a to-be-detected printed matter based on a line mod feature point positioning and registration algorithm; target image artifact elimination, respectively dividing the standard image and the target image after positioning and registration into a plurality of sub-blocks with the same size, and eliminating artifacts caused by localdeformation of the target image by using a sub-block neighborhood sliding artifact elimination method; extracting background region defects of the final difference image; extracting a contour of thestandard image and performing mathematical morphology expansion operation to obtain a contour mask, segmenting the final differential image into a contour area and a non-contour area by using a contour mask covering method, extracting and judging defects in the non-contour area and the contour area of the final differential image, and finally integrating, outputting and displaying the defects. Themethod can be used for successfully detecting the defects such as smudginess, incompleteness, ghosting, shifting, scratching and skip printing.

A fast splitting method for image includes the following steps: a) splitting the image into three parts of foreground area, unknown area and background area; b) calculating colour component F and B for foreground and background by setting any point C in unknown area as colour of according to the split areas; and c) adjusting colour value for F and B according to the estimated colour component of foreground and back ground, and finally to estimate alpha value of c point.

A method for automatically determining the region of interest from an image comprises the three steps of (a) analyzing content of the transformed coefficients of an image after a discrete signal transformation and partitioning an image into the interested region and background region that are based on p×p-pixel sub-blocks for performing classification; (b) locating the central point of the interested sub-blocks; and (c) integrating a plurality of the interested sub-blocks from said central point to the boundary of an image to generate a closed and continued region of interest by using a image processing technique with considering the bit-rate requirement.