249 results about "Image reduction" patented technology

A domain block extracting unit extracts a domain block image from an original image. A range block extracting unit extracts a range block image from an area in the vicinity of the domain block image. The range block image has size being larger than a domain size and being smaller than an enlarged size. A reduced range block forming unit reduces the range block image to the domain size to produce a reduced range block image. A similarity judging unit compares each of the reduced range block images with the domain block image to select the highest similarity range block image. An enlarged range block forming unit forms an enlarged range block image by enlarging the size of the highest similarity range block image to an enlarged size thereof. An enlarged image acquiring unit produces an enlarged image of an original image by employing the respective enlarged range block images.

On an operation panel, a preview image based on first preview image data generated by a first preview image generator is displayed (first stage), and then, a preview image based on second preview image data generated by a second preview image generator is displayed (second stage). An image reducing unit reduces input image data into an image size appropriate for the preview image to generate third preview image data. When image synthesis processing is set as user setting, an image processing unit changes, in accordance with the user setting, a display aspect of at least a portion of an area on the third preview image data corresponding to an area on the input image data in which another image data (a fixed pattern or the like) is to be synthesized.

A system and method for expansion and reduction of images uses an absolute value associated with each pixel of an input image (e.g., a color and/or intensity value) to determine a respective energy value for each pixel. For example, a given color or range of colors (e.g., skin tones, or other high-priority colors) may be assigned higher energy values than other colors and/or color ranges, and may be protected during image reduction and/or expansion. These energy values may be used to determine a cost associated with various seams of the image, which may represent the priority of the seams in the image. One or more low-cost seams may be identified for removal or replication to produce a resized image. The methods may be used in conjunction with an automated skin tone detector or a user interface that allows selection of one or more high priority colors or color ranges.

A failure analysis system includes an obtaining portion that obtains read-in image information that is image information obtained by reading an output image, a memory that stores fundamental image reduction information that is information in which an information amount of fundamental image information is reduced, the fundamental image information serving as a fundamental of the output image, a calculating portion that calculates a characteristic value of a projecting waveform by use of differential information between read-in image reduction information and the fundamental image reduction information, the read-in image reduction information being information in which the information amount of the read-in image information obtained by the obtaining portion is reduced, the fundamental image reduction information being stored in the memory; and a determining portion that determines a defect type group that is a group of defect types of elements included in the output image by use of a clustering process.

The invention discloses an image processing method and device. The image processing method is applied to a display unit comprising an optical amplification part. The method includes the steps that a marginal area in an image area is determined, and the image area except the marginal area serves as a middle area; image reduction processing is conducted on images in the marginal area in the image boundary direction; image magnification processing is conducted on images in the middle area in the image boundary direction; the images which are reduced and magnified are displayed through the display unit, and therefore the display unit can present images in the same proportion. According to the image processing method and device, under the effect of the optical amplification part, the images with the marginal areas reduced are magnified in vision, the magnification proportion of the images is equal to that of the images in the middle area, so that the display unit presents the images which are consistent in proportion, and therefore the images are displayed in a non-deformation mode in overall vision.

A video signal processing circuit uses a buffer memory for reducing or expanding video signals in the generation of child images to be displayed within a display window. Image size data, stored in a header within the buffer memory, and a reduced video signal are prevented from representing different image reduction ratios which might otherwise occur when the reduction ratio is changed. At the time of changing the reduction ratio, image size data SIZ are calculated from a write enable signal based on reduction ratio data K, for a one-field period just after the change by an input video clock generator 22. The calculated image size data are written to a header together with a reduced video signal in a field memory 2, and a flag bit SP indicating the change in the reduction ratio is also written to the header for the one-field period just after the change. When data are read from the buffer memory, the flag bit SP is detected by a display video clock generator 23 to mute a video signal output when there is a likelihood of displaying distorted data. On the other hand, writing to the field memory 2 is inhibited for the one-field period just after the change in the image magnification data so that the muting period of the video signal output can be shortened.

The invention discloses an image defogging method and system. The method comprises the steps: obtaining a fog image comprising a sky area; determining the sky area in the fog image; building an atmospheric scattering model; determining an atmospheric light value in the atmospheric scattering model according to the proportion of the sky area to the whole fog image, wherein the atmospheric light value is the atmospheric light intensity at an infinity place; determining the transmissivity of the fog image according to the atmospheric scattering model; and obtaining the observation intensity of the fog image. The method and system can carry out good defogging of the sky area in the fog image, are high in image reduction precision, are low in defogging complexity, and is high in processing speed.

Methods and systems of creating a photo-mask to form continuous relief micro-structures in photo-active material. This technology uses a basic amplitude mask or electron-beam to create a binary phase grating with pi-phase depth on a transparent reticle coated with photo-active material. The reticle is then used as a phase mask for the fabrication of analog micro-elements. The mask is used in an image reduction machine such as an optical stepper. The period and duty cycle of the phase gratings can be varied to create the proper analog intensity for the desired micro-profile on the photo-active material. The design, analysis, and fabrication procedure of this invention for prisms and positive micro-lenses has been demonstrated.

An image processing apparatus capable of executing filter processing with a desired blurring degree selected in accordance with an application from a multi-valued image captured an object surface, the image processing apparatus comprises: a first filter processing device for executing smoothing processing on the multi-valued image, a second filter processing device for creating a reduced image reduced from the multi-valued image with an image reduction ratio, executing smoothing processing on the reduced image, and creating an enlarged image of the smoothed image enlarged with an image enlargement ratio corresponding to the image reduction ratio, and an image display device for displaying a processed image by the first filter processing device or the second filter processing device.

An image processing apparatus for performing image reduction correction on target image data corresponding to pixels, includes a deletion position specifying unit configured to specify, as deletion positions of deletion pixels in the target image data, predetermined positions in image regions including the pixels having gradation values that are more than or equal to a predetermined density; and a pixel deleting unit configured to delete the deletion pixels at the deletion positions specified by the deletion position specifying unit, and to shift the pixels subsequent to the deletion pixels in a reduction direction as the deletion pixels are deleted.

The invention relates to the technical field of image processing, in particular to a method for measuring an average size of complicated particles based on Canny boundary detection. The method comprises the following steps of 1, inputting an image of moving particles; 2, performing Gaussian smoothing noise removal; 3, when the image size is greater than an image size threshold value, shrinking the image; 4, performing Canny boundary scanning, and converting the image into a binary image; 5, calculating the particle edge density of the image, and determining an average shape parameter of the particles and a background space parameter of the image; and 6, calculating the average size of the detected particles and the number of detected particles. through adoption of the method, the average size and the number of the particles in the image can be detected quickly and accurately; and the method is very suitable to statistics and measurement of a plurality of complicated particles at real time on line and can be used for pre-partitioning acomplicated particle image.

The invention relates to a adaptive image scaling method which comprises the following steps: Re size_xy is set as the scaling ratio, Thresi i=1, 2 is set as the threshold values, wherein Thres1 is more than Thres2; if Re size_xy is more than thres1, triple rational spline interpolation is adopted; if Re size_xy is more than Thres2, then weight triple rational spline interpolation is adopted; and as for other conditions, the image reduction algorithm based on a mapping image sub-block is adopted. On one hand, the new algorithm of multi-mode image scaling can self-adaptively choose a scaling algorithm according to the scaling ratio and enable the image scaling effect to achieve fine visual effect. On the other hand, the weight triple rational spline interpolation can improve the situations in which edge sawtooth emerges and part of information is lost after an image is reduced and maintain fine definition of other regions.

A photolithographic reduction projection catadioptric objective includes a first optical group having an even number of at least four mirrors and having a positive overall magnifying power, and a second substantially refractive optical group more image forward than the first optical group having a number of lenses. The second optical group has a negative overall magnifying power for providing image reduction. The first optical group provides compensative aberrative correction for the second optical group. The objective forms an image with a numerical aperture of at least substantially 0.65, and preferably greater than 0.70 or still more preferably greater than 0.75.

A system and method for expansion and reduction of images uses a look-up table to define an arbitrary mapping of data (e.g., pixel values) representing an image to respective energy values. Each pixel value may represent an absolute color or intensity value, a difference in color or intensity values, or an average, derivative, minimum, or maximum of two or more pixel values. The energy values may then be used to determine one or more low-cost seams of the image to be removed for an image reduction operation or replicated for an image expansion operation, where the cost of each seam is dependent on the energy values of the pixels of the seam. The look-up table may be used to apply a threshold and/or cap on the energy values mapped to pixel values. The look-up table may also provide a mechanism for reconfiguring mappings, thresholds, and/or caps.

The invention discloses a batch repair method aiming at damaged plant leaves. Firstly, image data is pretreated. The pretreatment comprises the following steps: image reduction -grayscale transformation - Gaussian filter - binarization; Contour trimming: canny edge detection -finding edge contour- circumscribing minimum quadrilateral - ROI region trimming; Watershed segmentation: foreground marking-background marking- unknown region marking- watershed segmentation; Then, the image to be repaired is replaced by the same color, and the mask of the region to be repaired is made. Finally, the repaired part is repaired by FMM algorithm. Compared with the prior art, the invention can complete the incomplete part of the leaf, has high repair accuracy, and avoids the influence of the leaf incomplete caused by the force majeure on the subsequent experiment. The invention solves the problem of batch production of a mask through a series of image preprocessing operations, and realizes batch processing operation of damaged plant leaves.

The present invention discloses a honeycomb core surface shape measurement data burr removal method. The method comprises the following steps of: obtaining three-dimensional surface shape data of a honeycomb core surface; arranging mobile windows in an integrated honeycomb measurement data xOy plane, only processing data covered by the mobile windows each time; establishing a plane image of the honeycomb core, and performing identification of apexes of the honeycomb core; performing image reduction for a certain proportion to identify the apexes; determining a threshold of a corner detection algorithm according to the measurement data; performing analysis of the identified apexes one by one, and determining honeycomb edges taking the apexes as end points; establishing search windows for analysis corner points; determining types of the analysis corner points; determining target corner points of the analysis corner points; establishing rectangular regions for the honeycomb edges; performing plane burr removal in each honeycomb edge measurement data; and performing space burr removal in each honeycomb edge measurement data.

An image processing apparatus includes a data supply node to receive line data scanned in a main scan direction of an image, an image enlargement unit coupled to the data supply node to apply to the line data an enlargement process for enlarging the image by an enlargement factor equal to an integer so as to produce enlarged data at an output node, and an image reduction unit coupled to the output node of the image enlargement unit to apply to the enlarged data a reduction process for reducing the enlarged image by a desired reduction factor so as to produce reduced data at an output node.

The invention discloses a human face key point positioning method. The human face key point positioning method comprises the following steps: carrying out human face detection on an objective image toobtain a human face image; shrinking the human face image into a shrunk image with preset definition; extracting a first-stage key point from the shrunk image by a supervision descending regressor; mapping the first-stage key point to the human face image so as to judge a three-dimensional posture of the human face image; and selecting the corresponding combined random tree regressor to extract asecond-stage key point from the human face image on the basis of the three-dimensional posture. By a mode of combination of a supervision descending method and a combined random tree algorithm, the human face key points in the image are positioned, and meanwhile, high precision and high speed are ensured.