Showing papers on "Image gradient published in 1996"

Method for embedding digital information in an image

Abstract: A method of embedding digital data in a source image includes the steps of: a) generating a multi-level data image representing the digital data; b) convolving the multi-level data image with an encoding carrier image to produce a frequency dispersed data image; and c) adding the frequency dispersed data image to the source image to produce a source image containing embedded data. The data is recovered from the image by: a) cross correlating the source image containing embedded data with a decoding carrier image to recover the data image; and b) extracting the digital data from the recovered data image.

Color indexing with weak spatial constraints

Abstract: To improve the discrimination power of color indexing techniques we encode a minimal amount of spatial information in the index. We propose an approach that lies between uniformly tesselating the images with rectangular regions and relying on fully segmented images. For each image we define 5 partially overlapping, fuzzy regions. From each region in the image we extract the first three moments of the color distribution and store them in the index. The feature vectors in the index are relatively insensitive to small translations and small rotations of an image because they are extracted from fuzzy regions. To retrieve images we define a function which measures the similarity of two color feature vectors. Invariance of retrieval results with respect to the typical image rotations of 90 degrees around the center of the image is guaranteed because our feature similarity function exploits the spatial arrangement of the 5 image regions. We present experimental results using an image database which contains more than 11,000 color images. Our experiments demonstrate clearly that our weak encoding of spatial information significantly increases the discrimination power of the index compared to plain color indexing techniques.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Method and apparatus for hiding one image or pattern within another

Abstract: A method of hiding a first image in a second image to produce a combined image includes the steps of: a) modifying the first image according to the content of the second image, so that when the modified first image is added to the second image to produce the combined image, no visible differences will exist between the second image and the combined image; and b) adding the modified first image to the second image to produce the combined image.

Method and apparatus for the automatic analysis of density range, color cast, and gradation of image originals on the BaSis of image values transformed from a first color space into a second color space

Abstract: A method and apparatus for analysis of an image original to be reproduced by evaluating image values (R, G, B) acquired by the point-by-point and line-by-line, trichromatic scanning. The image values of a first color space allocated to the input apparatus are transformed into image values of a second color space that is independent of the first color space. The analysis of the image original for calculating setting values for image processing is implemented on the basis of the transformed image values of the second color space. The master analysis on the basis of the image values is implemented in view of image scope, image gradation and/or color cast.

Vector order statistics operators as color edge detectors

Abstract: Color edge detection is approached in this paper using vector order statistics. Based on the R-ordering method, a class of color edge detectors is defined. These detectors function as vector operators as opposed to component-wise operators. Specific edge detectors can be obtained as special cases of this class. Various such detectors are defined and analyzed. Experimental results show the noise robustness of the vector order statistics operators. A quantitative evaluation and comparison to other color edge detectors favors our approach. Edge detection results obtained from real color images demonstrate the effectiveness of the proposed approach in real applications.

Image indexing and retrieval based on color histograms

Abstract: While general object recognition is difficult, it is relatively easy to capture various primitive properties such as color distributions, prominent regions and their topological features from an image and use them to narrow down the search space when attempts to retrieving images by contents from an image database are made. In this paper, we present an image database in which images are indexed and retrieved based on color histograms. We first address the problems inherent in color histograms created by the conventional method, and then propose a new method to create histograms which are compact in size and insensitive to minor illumination variations such as highlight, shape, and etc. A powerful indexing scheme where each histogram of an image is encoded into a numerical key, and stored in a two-layered tree structure is introduced. This approach turns the problem of histogram matching, which is computation intensive, into index key search, so as to realize quick data access in a large scale image database. Two types of user interfaces, Query by user provided sample images, and Query by combination of the system provided templates, are provided to meet various user requests. Various experimental evaluations exhibit the effectiveness of the image database system.

Textile fabric inspection system

Abstract: A method and apparatus for inspecting textile fabric which automatically detects defects within the field of view of a video camera. A frame of video information is captured and a digital image array is generated. A mask or operator is then used to generate a gradient image from the digital image array. The gradient image is then thresholded, dilated, optionally eroded, and then subjected to a blob analysis. A special operator is utilized in order to generate a gradient image which slow grey level transitions (e.g., oil spots) are identifiable.

Advances in automated 3‐D image analysis of cell populations imaged by confocal microscopy

Abstract: Automated three-dimensional (3-D) image analysis methods are presented for rapid and effective analysis of populations of fluorescently labeled cells or nuclei in thick tissue sections that have been imaged three dimensionally using a confocal microscope. The methods presented here greatly improve upon our earlier work (Roysam et al.:J Microsc 173: 115-126, 1994). The principal advances reported are: algorithms for efficient data pre-processing and adaptive segmentation, effective handling of image anisotrophy, and fast 3-D morphological algorithms for separating overlapping or connected clusters utilizing image gradient information whenever available. A particular feature of this method is its ability to separate densely packed and connected clusters of cell nuclei. Some of the challenges overcome in this work include the efficient and effective handling of imaging noise, anisotrophy, and large variations in image parameters such as intensity, object size, and shape. The method is able to handle significant inter-cell, intra-cell, inter-image, and intra-image variations. Studies indicate that this method is rapid, robust, and adaptable. Examples were presented to illustrate the applicability of this approach to analyzing images of nuclei from densely packed regions in thick sections of rat liver, and brain that were labeled with a fluorescent Schiff reagent.

Machine vision method and apparatus for edge-based image histogram analysis

Abstract: A system for edge-based image histogram analysis permits identification of predominant characteristics of edges in an image. The system includes an edge detector that generates an edge magnitude image having a plurality of edge magnitude values based on pixels in the input image (22). The edge detector can be a Sobel operator that generates the magnitude values by taking the derivative of the input image values, i.e., the rate of change of intensity over a plurality of image pixels. A mask generator (24) creates a mask based upon the values output by the edge detector. The mask can be used for masking input image values that are not in a region for which there is a sufficiently high edge magnitude. A mask applicator applies the pixel mask array to a selected image (25). A histogram generator generates a histogram of the pixel values in the masked image, i.e., a count of the number of image pixels that pass through the mask (26). A peak detector identifies the intensity value in the histogram that represents the predominant image intensity value or predominant edge direction values associated with the edge detected by the edge detector (27).

Automatic tone scale adjustment using image activity measures

Abstract: A method of automatically adjusting the tone scale adjustment for digital radiographic images. The method includes the steps of providing an input digital radiographic image; estimating the image noise as a function of code value of the image; determining the range of code values in the input image; determining which way the input image should be processed; determining a bounding box which contains the region of interest of the input image; computing the image activity histogram of the input image; determining four points from the image activity histogram; constructing the tone-scale curve for the input image; and mapping the input image through the tone-scale curve to produce an output image with good tone scale.

Robust search for image features across image sequences exhibiting non-uniform changes in brightness

Abstract: An apparatus and method for two-dimensional search for a model image within atest image that exploits edge-based matching of edge maps, followed by area-based matching of at least coarse resolution edge maps of respective multi-resolution edge-maps, to efficiently and accurately provide the position of at least one instance of the model image. The invention can find a location of the model image within each test image of a sequence of test images, even when there are non-uniform brightness changes in the test image due to process steps or lighting changes. The postion of each verified instance of the model image within the test image can be provided to an alignment device, a measurement device, or any other device that can use such position information.

Image processing apparatus for discriminating image characteristics using image signal information obtained in an image scanning operation

Abstract: An image processing apparatus generates color image signals representing an image of a scanned original document. A series of image discriminating units are provided. An edge discrimination unit discriminates edge regions with respect to each pixel. Further discrimination units discriminate other image regions, such as half tone regions, white background regions, photograph regions, or color regions, with respect to each pixel block. Discriminating results are stored in a memory to be used for subsequent image scans.

Producing a rendered image version of an original image using an image structure map representation of the image

Abstract: The invention automatically produces a rendered image version of an original image that accurately represents perceptually distinguishable objects, surfaces and edges in the original image. The original image is first converted to a unique data structure representation called an image structure map (ISM) that accurately, compactly and explicitly represents the geometry, topology and signal properties of perceptually distinguishable regions in the original image. The ISM is a dynamic partition of the image induced by a set of image region boundaries, and includes, for each region in the original image, a region data item that indicates the region boundary data items that form the region and a signal property descriptor indicating the value of signals computed for image locations in the region. An automatic segmentation operation determines image region boundaries occurring in the original image by analyzing discontinuities in signal values of original image locations. The topology of the rendered image version is accurate because vertices (endpoints and intersections) of image region boundaries are represented in the ISM in machine representable values that result from modifying exact vertex values using a rounding operation that mathematically ensures topological and geometric consistency with the original image. The method is particularly useful for producing rendered image versions of full color, continuous tone photographic images, and for producing line drawings of such images. The ISM representation of an image is, in most cases, more compact than its original raster form, and serves as a useful representation for archiving the image.

Apparatus and method for identification of tissue regions in digital mammographic images

Abstract: A method of identifying tissue regions in a digital image representing a body part provides a digital image representing a body part having tissue regions. The digital image is scaled by subsampling or interpolation, and texture extraction is applied to the scaled image to produce a plurality of texture images each having a different measure of the image texture. The texture images are clustered, and the clustered image is labeled based on both pixel intensity values and geometric adjacency of pixels. A threshold is applied to the labeled image, which is then filtered using a largest component filter system to determine the largest geometrically connected region in the threshold image. The filtered image is subjected to edge detection to produce an edge image containing only edge pixels at high code value, and the edge image is operated on to produce a convex hull image which outlines the skin line of the tissue region of the body part provided in the digital image.

Multichannel techniques in color image enhancement and modeling

Abstract: We present novel multichannel methods in two target research areas. The first area is color image modeling. Multichannel AR models have been developed and applied to color texture segmentation and synthesis. The second area is color image equalization, which is performed on the three RGB channels simultaneously, using the joint PDF. Alternatively, equalization at the HSI domain is performed in order to avoid changes in digital image hue. A parallel algorithm is proposed for color image histogram calculation and equalization.

Car Number Plate Detection With Edge Image Improvement

Abstract: In an automatic car number plate reading system, edge density can be used to successfully detect a number plate location for character recognition process due to the characteristics of the number plate. However the initial false detection rate will be increased along with the noise presented in a car image. A method is developed to improve the edge image by suppressing unwanted detail of a car image. It increases the Edge Density Discrimination in a car number plate location and reduces the initial false detection rate to optimize the detection performance.

Image display method, gradation conversion circuit, and image signal conversion apparatus

Abstract: An image display method displays an image by different gradation conversion in every pixel, on the basis of gradation frequency distribution of luminance of pixels near an edge of the image, and counting of gradation frequency of luminance of pixels near the edge is weighted depending on the coordinate values of each pixel so as to eliminate relative contrast drop in the image central part from the image peripheral parts

Model-based coding/decoding method and system

Abstract: A processing of causing a face image of a person A as an object of encoding to be deformed in correspondence to expression and motion of a face image of a person B as a reference image. The expression change and the motion from the model wire-frame are treated as fitting information, and this fitting information is made WA1 with respect to a first image of an object for photographing, while is made Wb1 with respect to a second image of an object for photographing. For example, the fitting information from a model wire-frame W00 to an image A1 is Wa1, and the fitting information from the image A1 to the model wire-frame W00 is Wa1. Next, an image A2 into which the first image A1 is caused to be deformed by a texture Ta1 of the first image A1 and a wire-frame function Wb1 Wa1 is obtained through composition. Texture mapping of sticking the texture Ta1 in correspondence to each of small areas of this wire-frame is carried out, whereby the image A2 into which the image A1 is caused to be deformed similarly to an image B1 is obtained through composition.

Methods and apparatus for detecting partial volume image artifacts

Abstract: The present invention, in one form, is a method for improving image quality in Computed Tomography systems by using a partial volume artifact estimation algorithm. In accordance with one embodiment of the algorithm, an object of interest is scanned to generate image data. The image data is segmented into low attenuation data and high attenuation data. A gradient image is generated for two adjacent slices of the image data. The gradient image is then forward projected and squared. The squared gradient image is an estimation of partial volume artifacts in the image data, and therefore is removed from the image data.

Fusion of color and edge information for improved segmentation and edge linking

Abstract: We propose a new method for combined color image segmentation and edge linking. The image is first segmented based on color information only. The segmentation map is modeled by a Gibbs random field, to ensure formation of spatially contiguous regions. Next, spatial edge locations are determined using the magnitude of the gradient of the 3-channel image vector field. Finally, regions in the segmentation map are split and merged by a region-labeling procedure to enforce their consistency with the edge map. The boundaries of the final segmentation map constitute a linked edge map. Experimental results are reported.

Image processor with image data compression capability

Abstract: In an image processor, image data of red, green and blue are converted to image data of lightness and chromaticities, and they are divided into pixel blocks. Then, image data of each block are compressed to data having 4 gradation levels smaller than 256 levels of the image data by generalized block truncation coding. Then, a capacity of image memory can be decreased. An attribute of the image data is decided for each block according to the compressed data. The attribute can be corrected by taking attributes of adjacent blocks into account.

Image pickup method, device and storage medium

Abstract: PROBLEM TO BE SOLVED: To easily obtain an accurately overlapped image through image pickup even in the case of panorama image pickup by storing at least part of an area of an image obtained by picking up the object and synthesizing a deformed image and the image obtained through image pickup via an image deformation step that deforms the stored image and displaying it. SOLUTION: An image pickup control section 3 controls each section to receive an object image formed by an image sensor 2 through an image pickup lens 1 as an electric signal and image data are obtained via an image signal processing section 4, an A/D converter section 5 and a color signal processing section 6. A panorama switch 12 is selected to pick up a right and a left image respectively and after prescribed processing based on a panorama mode signal, an image synthesis section 15 generate synthesis image data. An image deforming section 14 deforms a preceding image and an image synthesis section 15 synthesizes the preceding image with a succeeding image that is being picked up and the synthesized image is displayed on a display device 18 to allow the user to confirm it that both the images are accurately overlapped thereby easily realizing an accurately overlapped image.

Image processing apparatus and method for generating a control signal based on a discrimination of whether an input image includes a specific image

Abstract: A discrimination device and method that generates a control signal used for controlling a color image processing apparatus that processes color image data in a first color space and generates color image data in a second color space different from the first space. The color image data in the first color space is input and then a discrimination is performed to determine whether an image represented by the input color image data includes a specific image. A control signal is generated based on the discrimination result.

Method and apparatus for performing color conversion

Abstract: An image processing apparatus and method for performing color conversion on first image data of a first format to produce second image of a second format different from the first format. Each of the first and second image data represent a pixel of one of a stationary image and a moving image. The method and apparatus generate complementary color data from the first image data for each pixel of an image, determine a minimum and maximum value of the complementary color data, generate hue data representing a hue of each pixel of the image based on the complementary color data, the minimum value and the maximum value, and generate the second image data based on the hue.

A vector quantizer for image restoration

Abstract: An algorithm based on nonlinear interpolative vector quantization (NLIVQ) is presented which accomplishes image restoration concurrently with image compression The algorithm is applied to the problem of deblurring noise-free diffraction-limited images by training with a large set of blurred and original image pairs Simulation results demonstrate a quantitative improvement in images processed by the algorithm, as measured by image peak signal-to-noise ratio (PSNR), as well as a significant improvement in perceived image quality A theoretical formulation of the algorithm is presented along with a discussion of implementation, training and simulation results

Edge detection on object color

Abstract: In this paper a novel scheme for color edge detection is presented to minimize the false edge detection caused by specular reflection. The method is based on the dichromatic reflection model proposed by Shafer (1985) to describe the object reflection properties in the HSV color space, and is different from existing color edge detection techniques in three major aspects. First, our analysis accounts for multiple light sources and is less restrictive than techniques which are based on the assumption of single light source. Second, we have incorporated the V-component on top of the hue H to include the shading information which is absent in the latter. This effectively added in a new dimension in separating the regions which are similar in hue, but different in shade. Third, we had discovered that a single color edge operator is inadequate for detecting discontinuities in all conditions with equal precision. The V-component, for example, is more relevant than H in describing the edge contour when S is low, and vice versa. In between these two extremes, both components are found to have equal significance.

Determination of compatibility coefficients for color edge detection by relaxation

Abstract: In this paper, we propose a new algorithm which detects boundaries of objects from a color image. The result of this method is a binary image where only the boundary pixels are represented. This approach uses a co-operating relaxation process in order to enhance edge probabilities. The relaxation algorithm processes probabilities resulting from a gradient output of the different features of the color images. So, this algorithm is able to detect edges from variations of red, green and blue images. We present in the first part of this paper the relaxation scheme. In the second part, we propose two kinds of compatibility coefficients evaluations. These coefficients are compared in the third part of this paper using a rather complex image.

Matching Object Models to Segments from an Optical Flow Field

Abstract: The temporal changes of gray value structures recorded in an image sequence contain significantly more information about the recorded scene than the gray value structures of a single image. By incorporating optical flow estimates into the measurement function, our 3D pose estimation process exploits interframe information from an image sequence in addition to intraframe aspects used in previously investigated approaches. This increases the robustness of our vehicle tracking system and facilitates the correct tracking of vehicles even if their images are located in low contrast image areas. Moreover, partially occluded vehicles can be tracked without modeling the occlusion explicitly. The influence of interframe and intraframe image sequence data on pose estimation and vehicle tracking is discussed systematically based on various experiments with real outdoor scenes.