Showing papers on "Image gradient published in 1990"

Integrating region growing and edge detection

Abstract: A method that combines region growing and edge detection for image segmentation is presented. The authors start with a split-and merge algorithm wherein the parameters have been set up so that an over-segmented image results. Region boundaries are then eliminated or modified on the basis of criteria that integrate contrast with boundary smoothness, variation of the image gradient along the boundary, and a criterion that penalizes for the presence of artifacts reflecting the data structure used during segmentation (quadtree in this case). The algorithms were implemented in the C language on a Sun 3/160 workstation running under the Unix operating system. Simple tool images and aerial photographs were used to test the algorithms. The impression of human observers is that the method is very successful on the tool images and less so on the aerial photograph images. It is thought that the success in the tool images is because the objects shown occupy areas of many pixels, making it is easy to select parameters to separate signal information from noise. >

Variance‐based color image quantization for frame buffer display

Abstract: Color image quantization is a process of representing an image with a small number of well selected colors. In this article an algorithm for multidimensional data clustering (termed the variance-based algorithm), based on the criterion of minimization of the sum-of-squared error, is applied to the problem of reducing the number of colors used to represent a given color image. The suitability of the sum-of-squared error criterion for measuring the similarity between the original and quantized images is examined using a digitized image and a computer-generated image. The experimental results indicate that this error measure is basically consistent with the perceived quality of the quantized image. The performance of the variance-based algorithm is compared with that of other algorithms for color image quantization in terms of quantization images generated using the colors selected by the variance-based and the mediancut algorithms are also presented.

Video effects system able to intersect a 3-D image with a 2-D image

Abstract: A video effects system comprises a graphics generator for generating a three-dimensional image in simulated real time, a digital video effects device for generating a second image and transforming the second image in real time, and a depth combiner for combining the three-dimensional image with the transformed second image to produce an output image that is the intersection of the three-dimensional image and the transformed second image.

Image enhancement system

Abstract: A system for enhancing the quality of an image that suffers from staircase effects, contouring effects, and granular noise, without affecting the existing method of creating the image is disclosed. The enhancement system identifies the edge and nonedge regions in the decoded image, and then filters those regions in order to reduce the specific type of quality degradation that generally occurs in the specific type of region. The system is integrated into a processing system including means for receiving and displaying digital image data. The system receives the digital image data, differentiates between edge data and the nonedge data within the digital image data, and filters the image data accordingly. The filtered edge data and the filtered nonedge data are combined to form an enhanced image. A multi-pass filtering system is also disclosed.

Area discriminating system for an image processing system

Abstract: An area discriminating system for use in an image processing system capable of processing an image signal including character images signals and halftone images signals which determines the hues of the images represented by the image signal, produces hue present signals for each color of a selected number of colors which is a component of the hues of the images and a hue absent signals for each color of the selected number of colors which is not a component of the hues of the images, detects edge portions of images represented by the image signal, produces edge signals having values representing the edge portions, and produces edge emphasized signals for each hue included in the portion of the image represented by the edge signals. The image processing system further determines whether the image represented by the image signal is a halftone image or a character image and produces the edge emphasized signals further in accordance with the image determination.

Method and apparatus for detection of parallel edges in image processing

Abstract: A method and apparatus for detection of parallel edges in image processing systems is shown. A video source producing an image which is operated upon by Laplacian of Gaussian operator to produce an LOG image within which sign changes are detected to produce a zero crossing edge detected image. A vector gradient field of the LOG image is computed and subjected to a gradient field smoothing operation to produce a smoothed gradient field. The smoothed gradient field is examined to detect scaler minima within the field and the results thereof used to compute parallelism strength in accordance with preestablished criteria to generate a parallelism line image which is printed using a conventional printer.

Character and picture image data processing system

Abstract: An image processing system including image reading device such as an image scanner for reading an image on a document to produce image signals, a memory for storing the image signals, a data processing unit for processing the image signals. The data processing unit includes a character image discriminating function for discriminating a character image from a picture image, an image orientation detecting function for detecting orientation of the character image to determine whether the orientation of the character image is in a correct orientation, and an image rotation function for processing the image signals to rotate the image so that the image is correctly oriented.

Method for video-to-printing image resolution conversion

Abstract: A method of improving image resolution by interpolation combines the concept of convolution with a parameter-controlled mask, with the concept of adjustment of the mask based on edge information. In the method, first the edge information is extracted from the original image data, and then interpolated to the size to which the original image data will be interpolated. With the guidance of the interpolated edge information, the interpolation process will produce an image with high contrast but minimal artifacts. A spline-under-tension function is applied to generate interpolated values, the function being modified for image data points located close to edges.

Image layout apparatus for performing pattern modification such as coloring of an original image

Abstract: An image layout apparatus for recognizing a color frame selectively marked on an original image, and automatically laying out the original image includes a color frame discriminating circuit for discriminating an image signal corresponding to the color frame from an image signal corresponding to the original image, a to-be-laid-out image signal outputting circuit for extracting a specific image signal corresponding to a specific image defined by the color frame from the original image signal, and outputting the specific image signal as a to-be-laid-out image signal, and a layout processing circuit for performing predetermined layout processing such as coloring layout of the to-be-laid-out image signal in accordance with the color frame image signal.

Image processing apparatus for processing respective image data obtained by reading an outputting image signal corresponding to pixels forming the original image

Abstract: An image processing apparatus reads an original image by dividing it into pixels, processes respective image data obtained by the reading, and outputs an image signal corresponding to each pixel. The apparatus includes a selector for selecting minimum image data from image data of additive three primary colors obtained by reading a color image; a multiplying device for multiplying the minimum image data by either an under-color removal coefficient data or a black paint coefficient data supplied thereto and outputting under-color image data or black paint image data. An under-color removal calculator receives the image data of the additive three primary colors and the image data outputted from the multiplying device and generates under-color removal image data corresponding to the image data of the respective additive colors based on the under-color image data. A color correction masking device for receives the under-color removal image data from the under-color removal calculator and generates image data of subtractive colors based on masking coefficient data according to the respective additive colors. An image data selector receives the image data outputted from the multiplying device, the image data outputted from the color correction masking device, and one of the image data of the additive three primary colors so as to selectively output the respective image data.

Digital image generation

Abstract: A method of generating a representation of a subsidiary colored image initially contained within a color content of pixels of the image comprises defining a control data array. This control data array (9) defines, for at least those pixels in the image corresponding to the region containing the subsidiary image, the proportion of the image pixel color which is due to the subsidiary image. The average color in regions of the image different from the subsidiary image region is then determined. The inverse of the control data array is multiplied by the determined average color to generate a background image (13) which is subtracted (14) from the corresponding region of the original image so as to generate the representation of the subsidiary image.

A model-based approach for filtering and edge detection in noisy images

Abstract: The authors consider the problem of enhancement and edge detection on noisy, real-world images. The restoration and edge detection framework is based on an autoregressive (AR) random-field model. An edge is detected if the first and second directional derivatives and a local estimate of the variance at each point satisfy certain criteria. When noise is present, a good estimate of the original from the noisy images improves the signal-to-noise ratio, resulting in better estimates of the directional derivatives. To avoid excessive computation, the problem of estimation of the original image and the model parameters is presented as a combination of a reduced-update Kalman filter and an adaptive-least-squares parameter estimation algorithm. The restoration process is completed with a min-max replacement scheme to enhance edge strength. An orientation-sensitive detector resulting from the use of an AR model may not detect edges of significantly different orientations. This is partially overcome by running four edge detectors on the four interior pixels of a 4*4 window; this corresponds to rotating the window in successive multiples of 90 degrees . Comparisons with R.M. Haralick's (1984) facet model edge detector, R. Nevatia and K.R. Babu's (1980) line finder, and J. Canny's (1986) edge detector are given. >

Still image processing method for blurring an image background and producing a visual flowing effect

Abstract: A still image processing method which can execute the effective flowing process is provided. In this method, when the flowing process is executed by shifting some or all of the pixels constituting a still image of one image plane in a predetermined direction, if no image information to be shifted exists at the first image position, the image information from elsewhere in the image plane is shifted to the second image position. The image information at the second image position is obtained by shifting the image information in the image plane in the direction opposite to the principal shifting direction.

A Moment-based Three-dimensional Edge Operator

Abstract: A three-dimensional edge operator for detecting anatomical structures in medical imaging is presented. It uses the spatial moments of the gray-level surface, and operates in three dimensions with any window size. It allows the location and the contrast surface, as well as the surface orientation, to be estimated. The computation of the discrete version is reported. Bias and errors due to the spatial sampling and noise are analyzed at both a theoretical and experimental level. The moment-based operator is compared with other well-known edge operators using simple shaped primitives for which the analytical solution is known. The 3-D rendering of real data is then provided by merging the operator in a ray-tracing framework.<>

An X-ray image processing device

Abstract: An X-ray image processing device using dual energy (1,2) projection radiography method, wherein the low energy image and the high energy image are subjected to a subtraction (7) processing to output a first image such as a soft tissue X-ray image, and the first image and the low energy image are subjected to another subtraction (8) to output a second image such as a bone X-ray image without deterioration of the X-ray image.

Normalized edge detector

Abstract: A normalized Gaussian operator that can be separated into normalized functions in the x and y directions is presented. The behavior of the gradient values of step and ramp edges and combinations of pairs of these idealized edges obtained using this operator are analyzed. It is shown that the slope of a ramp edge can be estimated using the gradient operator at a single small scale and that the contrast and width of a ramp can also be estimated using only gradient information. Thus, the gradient is shown to contain much more information than is typically used in gradient-based edge detectors. Simulations were performed on ideal edges and edge pairs to demonstrate the actual behavior of the operator for intermediate values. The operator was also applied to real images, and slope, contrast, and scale were obtained at gradient maxima points. >

Method of adjusting image processing conditions

Abstract: In a method of adjusting image processing conditions for use in processing of final read-out image signals obtained by final read-out carried out for detecting the image signals used in reproduction of a visible image from a recording medium carrying a radiation image recorded thereon by limitation of an irradiation field, a histogram of the final read-out image signals obtained by the final read-out is created. Prospective edge point signals which are considered to be signals representing edge portions of the irradiation field are detected from the final read-out image signals. A region of a lever lower than the level of a characteristic value representing the prospective edge point signals is removed from the histogram, and the image processing conditions are adjusted on the basis of the histogram outside of the lower level region.

Image processing apparatus for texture processing

Abstract: An image processing apparatus performs texture processing, wherein second image data is modulated in accordance with first image data, and a density of the output image is adjusted appropriately by adjusting a D.C. level or a A.C. level of the modulated second image data.

A spatio-temporal generalization of Canny's edge detector

Abstract: Moving step edges are modeled as the product of a deterministic function in space and a stochastic function in time which captures the edge shapes and the temporal uncertainties, respectively Under J Canny's (IEEE Trans on Pattern Analysis and Machine Intelligence, volPAMI-8, p679-98, Nov 1986) original optimality criteria, a set of optimal edge detectors is derived They are in a product form, ie, a product of a spatial function and a temporal function The spatial function is Canny's edge detector in one dimension and the temporal function can be well approximated by the exponential function Generalizing Canny's edge detector to the temporal domain is not only theoretically interesting, but also practically useful The generalization of Canny's edge detectors provides better immunity to noise and can serve as one of the tools in understanding the temporal behavior of moving edges They have been used in a data-fusion framework to detect moving edges and their normal velocities simultaneously For completeness, the authors derive some properties of the optimal edge detectors and compare them with Gabor filters >

Method and apparatus for converting a line density of a bi-level image signal

Abstract: A correspondence relation between a structure of a bi-level pattern A and a structure of a bi-level pattern B is statistically learned by use of a learning high-density image. The bi-level pattern A forms a partial region of a low-density character and line image except a screened dot image. The bi-level pattern B forms a corresponding partial region of a desired high-density image. A judgement is made as to whether the low-density image is equal to or different from a screened dot image. Reference pixels are selected from the partial region of the low-density image. The low-density bi-level pattern A is converted into the high-density bi-level pattern B on the basis of a result of the learning by use of the selected reference pixels when the low-density image is different from a screened dot image. A pixel of the low-density image is repeated to convert the low-density image into the high-density image when the low-density image is equal to a screend dot image.

Image processing apparatus including binary data producing unit

Abstract: An image data processing apparatus binary-codes an image signal obtained from an image sensor of the CCD type or the like so as to output a binary-coded image signal. The image signal obtained from the image sensor A/D-converted into digital image data. Based upon the digital image data, average values of luminance values of the digital image data are calculated for an array of pixels in a preselected area of the CCD. This average value is used as a threshold level for binary coding the image data for these pixels at the center portion of this preselected area. Furthermore, to detect coutours this data processing apparatus calculates a gradient in the luminance values of the pixels in a portion of the preselected area of the CCD in an X direction and a Y direction, and the gradient value is used to obtain binary-coded data in accordance with the above-described method.

Process for determining the instantaneous position and shape of moving objects and for displaying them as a binary image

Abstract: In the process described, images of the moving objects are recorded at intervals of time using a stationary camera, and an image sequence generated from these recordings. From the difference between this image sequence and a reference sequence, a difference sequence is generated. The difference sequence is binarised using a threshold value, and binary object masks are generated. The reference image sequence is generated recursively in time by virtue of the fact that a reference image associated with an image depends on the difference between the image preceding this image and the reference image associated with the image preceding the image, the initial reference image having a selectable value. The reference image sequence is thus dependent only on the current image and the reference image, so the system adapts to slow changes in image intensity. Faulty detections are avoided.

Method for controlling coding variable of image signal

Abstract: PURPOSE:To reduce the variation of a coding variable due to the characteristics of an image by using the displacement of an image whose forecasting image is to be generated from a reference image to control the coding variable of an image signal. CONSTITUTION:A reference image is set up in each frame interval or field interval of an image signal and a forecasting image for an image to be formed between the reference images is generated based upon the reference images. In this case, the coding variable of an image signal is controlled by using the displacement of the image whose forecasting image is to be generated from the reference image. Namely, the forecasting image of each inter-data is generated by a movement compensation forecasting device 4 based upon intra-data. Consequently, the coding variable can be changed in accordance with a sudden change in the image or the change of scenes and the variation of the coding variable due to the characteristics of the image can be reduced.

Nonlinear filter derived from topological image features

Abstract: A digital machine-inspection system is being developed at Oak Ridge National Laboratory to detect flaws on printed graphic images. The inspection is based on subtraction of a digitized test image from a reference image to determine the location, number, extent, and contrast of potential flaws. When performing subtractive analysis on the digitized information, two sources of errors in the amplitude of the difference image can develop: (1) spatial misregistration of the reference and test sample, or (2) random fluctuations in the printing process. Variations in printing and registration between samples will generate topological artifacts related to surface structure, which is referred to as edge noise in the difference image. Most feature extraction routines require that the difference image be relatively free of noise to perform properly. A novel algorithm has been developed to filter edge noise from the difference images. The algorithm relies on the a priori assumption that edge noise will be located near locations having a strong intensity gradient in the reference image. The filter is based on the structure of the reference image and is used to attenuate edge features in the difference image. The filtering algorithm, consisting of an image multiplication, a global intensity threshold, and an erosion/dilation, has reduced edge noise by 98% over the unfiltered image and can be implemented using off-the-shelf hardware.© (1990) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Tomographic image processor

Abstract: PURPOSE: To satisfactorily decrease the flowing images with the image time held as it is by simulating the flowing image emerging in the image of a 1st fault face with use of the image data on another fault face parallel to the desired 1st fault face. CONSTITUTION: The flowing image emerging in an image 3 of a 1st fault face is simulated to obtain an image. Then the 2nd image data SB showing the simulated image is obtained based on the image data S 1 , etc., except the 1st image data S 3 showing the image 3 of the desired 1st fault face out of those image data S 1 - S 5 showing the images 1 - 5 of fault faces respectively. Then the 3rd image data SR showing an image where the flowing images are decreased or eliminated is obtained based on the data SB and the data S 3 . Thus the flowing images are decreased or eliminated with the effective image information held as it is. COPYRIGHT: (C)1991,JPO&Japio

Method for determining image points in object images

Abstract: A method for determining an image point in an object image composed of the steps of detecting an image signal made up of a series of image signal components representing respective picture elements in a radiation image, which includes an object image and which has been recorded on a recording medium. The center of gravity of the object on the recording medium is found from the image signal by weighting the respective picture elements with corresponding absolute values of differentiated values resulting from the carrying out of differentiation processing on the image signal values corresponding to the respective picture elements. A position, at which the center of gravity is located, is determined as the image point in the object image.