Showing papers on "Image gradient published in 1995"

A deformable-template approach to lane detection

Abstract: Vision-based algorithms for locating lane boundaries without a prior model of the road being viewed need to be able to operate robustly under a wide variety of conditions, including cases where there are large amounts of clutter in the image. This clutter can be due to shadows, puddles, oil stains, tire skid marks, etc. This poses a challenge for edge-based lane detection schemes, as it is often impossible to select a gradient magnitude threshold which doesn't either remove edges of interest corresponding to road markings and edges or include edges corresponding to irrelevant clutter. The approach taken in this work is to use a deformable template model of lane structure to locate lane boundaries without thresholding the intensity gradient information. The Metropolis algorithm is used to maximize a function which evaluates how well the image gradient data supports a given set of template deformation parameters. The result, the LOIS lane detection algorithm (likelihood of image shape), is able to detect lane markings in situations with strong mottled shadows and broken or interrupted lane markings which would pose problems for algorithms which use local, thresholded edge information.

Image encoding and decoding method and apparatus using edge synthesis and inverse wavelet transform

Abstract: A digitized image is encoded by detecting edges in the image, encoding the position and sharpness of the detected edges, filtering the image by a low-pass filter to generate a low-frequency image, and encoding the low-frequency image. A digitized image encoded in this way is reconstructed by generating a horizontal edge image and a vertical edge image from the encoded edge position and sharpness information, synthesizing a pair of high-frequency images by filtering the horizontal and vertical edge images with an edge synthesis filter, decoding the low-frequency image, and performing an inverse wavelet transform on the decoded low-frequency image and the high-frequency images.

A Comparative Study On Color Edge Detection

Abstract: Several approaches of different complexity already exist to edge detection in color images. Nevertheless, the question remains of how different are the results when employing computational costly techniques instead of simple ones. This paper presents a comparative study on different approaches to color edge detection. The approaches are based on the Sobel operator, the Laplace operator, the Mexican Hat operator, different realizations of the Cumani operator, and the Alshatti-Lambert operator. Furthermore, we present an efficient algorithm for implementing the Cumani operator. All operators have been applied to several synthetic and real images. The results are presented in this paper. We show that the quality of the results increases if Gaussian masks of larger width are used in the derivation process instead of simple 3 x 3 masks as suggested in the underlying papers. Moreover, multiresolution approaches can be applied to color images when using Gaussian masks with different standard deviations in the edge detection scheme.

Segmentation based image compression system

Abstract: An image processing system encodes a natural image into a segmented or mosaic image having well-defined edges and a residual image. The segmented image is encoded using a lossless encoding technique while the residual image is encoded using a lossy technique. This encoded image may be recorded on a video tape such that the segmented image may be recovered in picture-in-shuttle modes such as fast forward and fast rewind. In addition, the recorded image may be decoded and reencoded through several generational levels without experiencing significant degradation in perceived image quality. The segmented image is produced by an encoder which employs a multi-scale edge finder that is able to resolve transitions occurring over two, four and eight pixels into an edge located between two pixels. In addition, the lossless encoder includes circuitry which chain-encodes the segmented image into a low-resolution image and multiple complementary images such that the low-resolution image may be stored as a single data packet and, thus, recovered as a unit from the tape in picture-in-shuttle mode.

Image processing apparatus for performing adaptive data processing in accordance with kind of image

Abstract: An image processing apparatus includes an image input section, a color image/monochrome image converting section for performing image area division, a binarization circuit for binarizing a converted monochrome image, a reducing section for reducing a binary image, a boundary extracting section for extracting the boundaries between the areas of constituent elements constituting an input image, e.g., a binary image and a continuous gradation image, and a kind-of-image determining section for determining the kinds of images in partial areas defined by the extracted boundaries. For example, the image processing apparatus further includes a data compressing section. In the image processing apparatus, pre-processing is performed to efficiently performing pattern determination in consideration of localization of frequencies of occurrence of edges and black pixel patterns of an image, and kind-of-image determination is performed by a neural network on the basis of the data obtained by pre-processing, thus performing suitable processing such as data compression in accordance with the determination result.

Edge and line feature extraction based on covariance models

Abstract: Image segmentation based on contour extraction usually involves three stages of image operations: feature extraction, edge detection and edge linking. This paper is devoted to the first stage: a method to design feature extractors used to detect edges from noisy and/or blurred images. The method relies on a model that describes the existence of image discontinuities (e.g. edges) in terms of covariance functions. The feature extractor transforms the input image into a "log-likelihood ratio" image. Such an image is a good starting point of the edge detection stage since it represents a balanced trade-off between signal-to-noise ratio and the ability to resolve detailed structures. For 1-D signals, the performance of the edge detector based on this feature extractor is quantitatively assessed by the so called "average risk measure". The results are compared with the performances of 1-D edge detectors known from literature. Generalizations to 2-D operators are given. Applications on real world images are presented showing the capability of the covariance model to build edge and line feature extractors. Finally it is shown that the covariance model can be coupled to a MRF-model of edge configurations so as to arrive at a maximum a posteriori estimate of the edges or lines in the image. >

Method and apparatus for the analysis and correction of the image gradation in image originals

Abstract: A method and apparatus for the analysis and correction of the image gradation of an image original to be reproduced by evaluating image values acquired by point-by-point and line-by-line, optoelectronic scanning with an input device in apparatus and systems for image processing. The image original is geometrically subdivided into a plurality of sub-images. The frequency distribution of the image values or, respectively, of the luminance components of the color values in a corresponding sub-image is separately identified as a sub-image histogram. The sub-image histograms of the individual sub-images are evaluated and the sub-images relevant for the image gradation are identified by means of the evaluation. An aggregate histogram that corresponds to the frequency distribution of the image values or, respectively, of the luminance component of the color values in the relevant sub-images is calculated from the sub-image histograms of the relevant sub-images. Correction values for the correction of the image gradation characteristic of the image original are subsequently calculated from the aggregate histogram according to the method of histogram modification.

Image combining method and apparatus

Abstract: In image combining method of phototaking an object to be photographed by using a plurality of image taking systems with portions of fields of view thereof overlapping, and forming combined image information by combining pieces of image information obtained by the image taking systems, coordinates changing processing is performed by using the distance information of an object to be photographed, and image signals output from the respective image taking systems are compensated in accordance with the changed coordinates. One of the compensated image signals is selected with respect to a region where a far-distance portion of the object is concealed by a near-distance object, of the overlapping region of a combined image signal. With this operation, a plurality of image signals output from the respective image taking systems are combined into one image signal output in a state defined by an arbitrary object distance and the imaging magnification from an image taking system in which the viewpoint position and the optical axis direction are defined by the shift amount of the viewpoint position from each image taking system and the convergence angle of the optical axis.

Method and apparatus for expanding the dynamic range of sensed color images

Abstract: Disclosed is an image processing method of expanding the dynamic range by determining a saturated or noise region in an image signal and replacing the image signal with a proper image signal. A threshold value is set in units of colors on the basis of a standard image signal for each color, which is obtained upon sensing an image in a standard exposure, and a non-standard image signal for each color, which is obtained upon sensing the image in a non-standard exposure. A saturated or noise region is determined by applying the threshold value set in units of colors to the standard image signal. A region determined as a saturated or noise region is replaced with the non-standard image signal.

Multiresolution sequential edge linking

Abstract: We describe a multiresolution approach to edge detection using a sequential search algorithm. The use of a multiresolution image pyramid allows the integration of global edge information contained in lower resolutions to guide the sequential search at higher resolutions. As a consequence, the dependence on a priori knowledge of the image edges is greatly reduced. Estimating the sequential search parameters from lower resolution images provides for a more accurate and less costly search of edge paths in the image.

The local K-means algorithm for colour image quantization

Abstract: Colour image quantization is the process of representing an image with a small number of well selected colours. Most previous colour quantization techniques use a recursive pre-clustering approach. These algorithms subdivide the colour space into a set of simple geometric regions. Thus, the colour map is chosen on the basis of this approximation. We propose a new quantization method called local K-means (LKM).1t is an iterative post-clustering technique that approximates an optimal palette using multiple subsets of image points. The paper also presents ways to speedup the search of the closest colour for a dynamically changing palette. The local K-means procedure is compared with popular pre-clustering algorithms. The LKM method is able to generate a high quality palette significantly fast er than other quantization techniques.

Method for enhancing ultrasound image

Abstract: Ultrasound gray-scale image data and corresponding processed gray-scale image data are color-enhanced to generate an enhanced multi-color image At one step, a color map look-up table is defined from the processed gray-scale image data to define a color palette of K colors, (eg, K=4-16) Histogram analysis, nonlinear mapping or segmentation processing is used to map the gray-scale levels to the color palette The processed gray-scale image data then is transposed into a transposed color image data set Data interpolation then is performed in which each pixel of the original gray-scale image data is interpolated with a corresponding pixel among the transposed color image data set Interpolation weighting is adjustable by the user to determine how much detail from the original gray scale image is preserved

Edge detection of color images using the HSL color space

Abstract: Various edge detectors have been proposed as well as several different types of adaptive edge detectors, but the performance of many of these edge detectors depends on the features and the noise present in the grayscale image. Attempts have been made to extend edge detection to color images by applying grayscale edge detection methods to each of the individual red, blue, and green color components as well as to the hue, saturation, and intensity color components of the color image. The modulus 2(pi) nature of the hue color component makes its detection difficult. For example, a hue of 0 and 2(pi) yields the same color tint. Normal edge detection of a color image containing adjacent pixels with hue of 0 and 2(pi) could yield the presence of an edge when an edge is really not present. This paper presents a method of mapping the 2(pi) modulus hue space to a linear space enabling the edge detection of the hue color component using the Sobel edge detector. The results of this algorithm are compared against the edge detection methods using the red, blue, and green color components. By combining the hue edge image with the intensity and saturation edge images, more edge information is observed.

Method and system for editing multiresolution images at fractional-levels of resolution using a wavelet representation

Abstract: A method and apparatus for editing an image having different levels of resolution in different places. The method has the steps of inputting data representing the image, displaying at least a portion of the image at a fractional-level between the levels of resolution. The method also has the steps of editing the image at the fractional-level of resolution, updating the image to create an edited version of the image, storing the edited version of the image, and outputting the edited version of the image.

Image processing device providing improved image data processing by converting original image into a plurality of pixels and analyzing density data of each pixel

Abstract: An image processing device in accordance with the present invention processes image data obtained by reading an original image including an image portion and a background portion to subdivide the original image into a plurality of images, the image data including density data representing density of each image. The device includes a device for outputting background density data, a device for outputting density coefficient data, a background color removing device for decreasing a value of density data corresponding to the background portion based on the background density data, and a density correcting device for increasing a value of density data corresponding to the image portion based on the density coefficient data.

Adaptive X-ray brightness and display control for a medical imaging system

Abstract: An x-ray imaging system includes a source of x-rays, a video camera which produces an image signal formed by x-ray attenuation values, and image signal processor and a video monitor for displaying the x-ray image. The system also has an automatic image control that includes a peak detector, an average brightness detector and a transfer function generator for the image processor. The peak detector receives the image signal and produces a video gain control signal for controlling the video camera in response to a comparison of a peak level of the image signal to a peak reference level. The average the brightness detector employs the image signal to produce a feedback signal which controls by the source of x-rays. The transfer function generator produces a histogram of intensity levels in the image signal which histogram forms a look-up table that is used by the image processor to transform the image signal into the adjusted image signal for display.

Method and apparatus for gradation correction and image edge extraction

Abstract: The present invention relates to an image processing apparatus in which gradation correction on each partial region is performed between an image input means and an edge extracting means so that an edge of a region within an image is accurately extracted. An image dividing means 2, which had already learned a relationship between the condition of an image and the necessity of image division so as to judge the condition of the image based on learning results and divide the image appropriately, divides an input image from an image input means 1 into a plurality of image blocks. An image correction information extracting means 3 calculates correction information on each image block. A gradation correction means 4, which had already learned a relationship between correction information and non-linear correction curves to judge correction information based on learning results and perform gradation correction on a target image block using a selected curve, performs gradation correction and enhances an edge which is to be extracted. An image synthesizing means 5 recombines the respective corrected image blocks. An edge extracting means 6 extracts an edge from a synthesized image. An image output means 7 outputs an edge image.

Image processing apparatus for converting a color image into a pattern image with a line having a width which is equal to or less than a predetermined width not being converted

Abstract: An image processing apparatus for converting color images into monochromatic pattern images. The image processing apparatus includes: means for detecting the area of a color image; means for converting a color image into a monochromatic pattern image; and control means for varying such image processing in accordance with the result of detection made by the means for detecting the area. When a thin line is detected in a color area, the method of processing is determined based on the width of the detected thin line. For example, when the width of the thin line is smaller than a predetermined value, the area of such thin line may be outputted as a plain image instead of a pattern image so that it may easily be seen or recognized. The contour of a color area may be made conspicuous by combining a plain image and a pattern image.

Method and recording medium for separating and composing background and character image data

Abstract: An image processing method for automatically executing operation steps of repairing a defect of an image of a document which is read by a scanner and changing a background image in a short time and a recording medium for storing them. An image processing method comprising a step of separating background image data from said image data by processing by a maximum filter for comparing the brightness of each pixel constituting said image data with the brightness of peripheral pixels and replacing it with the maximum brightness; and a step of separating character and figure image data by subtracting the background image data obtained by the above step in (a) from the above image data.

Binary image processor

Abstract: A low cost binary image processor in an image processing apparatus designed to perform the shading correction and binarize the edge emphasis of an image with an automatic gain control according to background intensity using half-tone processing. This binary image processor comprises an image sensor for reading an image from a document, a converter for converting an electric signal read-out from said image sensor into image data, a threshold generator for generating a threshold value corresponding to each input pixel of the image data, an image processor for correcting shading and emphasizing edge of said image data to produce processed data having said shading corrected and edge emphasized on a line-by-line basis, and a binarizing circuit for using half-tone processing to binarize each pixel of the processed data on a basis of said threshold value and generate binary data accurately representing the image.

Lane Boundary Detection Using Deformable Templates: Effects of Image Subsampling on Detected Lane Edge

Abstract: In order to be robust, a system for detecting road lane boundaries in images needs to be able to handle scenes which contain large amounts of clutter due to shadows, puddles, oil stains, skid marks, leaves and dirt on the road, etc. Many prior systems threshold the image gradient magnitude to detect edges, and then use the detected edge points to identify the lane boundaries. This can result in a very noisy edge image, as there are many situations in which there are strong edges in the image due to irrelevant clutter. There are also many situations in which the edges of the features defining portions of the lane boundaries have a lower intensity gradient than distracting clutter edges in the image. The LOIS (Likelihood of Image Shape) lane detection algorithm solves this problem by using a deformable template approach that uses image intensity gradient information in a way which does not require thresholding. This paper describes the LOIS algorithm in detail, and shows the results of applying the algorithm to a number of challenging scenes. Images are included comparing the lane boundaries detected by applying LOIS to a 240×256 image with the lane boundaries detected by applying the algorithm to a 30×32 subsampled version of the same image. Qualitatively the results are very similar, but the algorithm runs 45 times faster on the subsampled images.

Image detection and background processing device and method

Abstract: An image detection and background processing device and method having a image reader for reading a whole document and converting the read document to a digital image data of multi value. The image forming apparatus detects the density of a background in the document based on the digital image data obtained by the image reader, sets a reference value based on the background density as well as the distribution of the digital image data, and distinguishes an image area of the document from the background by comparing the reference value and the image data so as to execute a process concerning the distinguished image area (for example, an automatic magnification selection process or an automatic paper selection process). The apparatus and method includes analysis capability for determining whether the background area can be accurately discriminated from the image area based on image data.

Image synthesis method and image synthesizer

Abstract: PROBLEM TO BE SOLVED: To obtain the image synthesis method and the image synthesizer in which plural images having different image states due to difference from an image pickup condition or the like are synthesized in an excellent way. SOLUTION: Gradation conversion sections 31, 32 correct input images a, b depending on image states in an overlapped image area. In this case, gradation conversion is applied to the input images a, b, to correct them so that the lightness in the overlapped image area of the two images is made equal. Furthermore, an image conversion synthesis section 50 conducts synthesis processing so that the center of the overlapped part comes to a joint and the input images a, b whose lightness is corrected by the gradation conversion sections 31, 32 are converted by a conversion parameter and the result is synthesized into one image.

Image processing system and method for formatting compressed image data

Abstract: Image data are defined by color vectors each composed of vector factors. Each vector factor specifies the brightness and color difference of a dot. The image data are transmitted with a normal timing when the vector factors correspond to dots of the image one for one, and are transmitted with another timing in another case to scroll the image horizontally.

Image processing method and device employing same

Abstract: An image processing method and device by which objects (6) supplied successively on a conveyor belt (1) or other means of conveyance are imaged individually and image processing is performed on the images so obtained. Image processing is performed, for example, to compare markings on an object image with a model image to identify variations between the two images. If variations are detected, the model image in memory can be modified or replaced with the input object image without shutting down an entire production line in order to create an entirely new model image. In this way the recorded model data can be updated without interrupting the flow on the belt (1), and appropriate correction data can be recorded efficiently.

Isophotes: The Key to Tractable Local Shading Analysis

Abstract: When studying the formation of intensity image of an opaque surface, a natural question arises: how does the local surface structure project on the local image structure? We consider this question for the case of a single and monocular intensity image. In this paper, we discuss the the general problem of local shading analysis (LSA) of an arbitrary C2 surface. We reformulate the problem so that it is well tractable without any restrictive assumptions about the surface. We also contribute to the discussion about the LSA ambiguity problem by identifying image structures where the local surface interpretation may only change.

A method for enhancing the picture quality of low bit-rate block-coded images

Abstract: We describe a post-processing method which is designed to remove the picture impairments typically introduced by spatial domain block coding techniques, such as vector quantization (VQ) and block truncation coding (BTC). In these coding methods, the quantization noise is highly correlated with the characteristics of the original signals, so that different areas of the coded image suffer from distinctly different impairments. In particular, uniform areas suffer from the blocking effect, where the boundaries of adjacent blocks become visible resulting in false contours. Moreover, all diagonal edges appear jagged, which is known as the staircase effect. Finally, most of the textured areas are 'washed-out'. The post-processing method exploits the properties of smoothed image gradient data to distinguish between high and low detail regions of the decoded image. The filtering process is then decided based on the region classification. For the high detail image areas, which include edges and texture, a fully adaptive Gaussian-type filter is employed. The shape and the position of the Gaussian kernel is adapted according to the characteristics of each local region. For the low detail image regions, which include areas of constant or slowly varying intensity, a simple Gaussian smoothing operator is used. Simulation results confirm that, after applying this post-filtering algorithm to the coded images, the annoying blocking effect is reduced and the jagged edges appear continuous and sharp.

Method and apparatus for rendering halftone areas of an image with continuous boundaries

Abstract: A method and apparatus are disclosed for locating and coloring true boundaries of image elements forming a color image defined with colors having one or more color separations. Once a boundary of an image element is located and determined to be a true boundary of the color image, the original color of the image element boundary is mapped to a solid color so that ragged edges created when rendering certain colors are minimized when reproducing. the color image element.