Showing papers on "Grayscale published in 2001"

Contour and Texture Analysis for Image Segmentation

Abstract: This paper provides an algorithm for partitioning grayscale images into disjoint regions of coherent brightness and texture. Natural images contain both textured and untextured regions, so the cues of contour and texture differences are exploited simultaneously. Contours are treated in the intervening contour framework, while texture is analyzed using textons. Each of these cues has a domain of applicability, so to facilitate cue combination we introduce a gating operator based on the texturedness of the neighborhood at a pixel. Having obtained a local measure of how likely two nearby pixels are to belong to the same region, we use the spectral graph theoretic framework of normalized cuts to find partitions of the image into regions of coherent texture and brightness. Experimental results on a wide range of images are shown.

Robust Face Detection Using the Hausdorff Distance

Abstract: The localization of human faces in digital images is a fundamental step in the process of face recognition. This paper presents a shape comparison approach to achieve fast, accurate face detection that is robust to changes in illumination and background. The proposed method is edge-based and works on grayscale still images. The Hausdorff distance is used as a similarity measure between a general face model and possible instances of the object within the image. The paper describes an efficient implementation, making this approach suitable for real-time applications. A two-step process that allows both coarse detection and exact localization of faces is presented. Experiments were performed on a large test set base and rated with a new validation measurement.

Reliable detection of LSB steganography in color and grayscale images

Abstract: A large number of commercial steganographic programs use the Least Significant Bit embedding (LSB) as the method of choice for message hiding in 24-bit, 8-bit color images, and grayscale images. It is commonly believed that changes to the LSBs of colors cannot be detected due to noise that is always present in digital images. In this paper, we describe a new very accurate and reliable method that can detect LSB embedding in randomly scattered pixels in both 24-bit color images and 8-bit grayscale or color images. It is based on our previous work on lossless data embedding [1]. By inspecting the differences in the number of regular and singular groups for the LSB and the "shifted LSB plane", we can reliably detect messages as short as 0.03bpp.

A Generalized Local Binary Pattern Operator for Multiresolution Gray Scale and Rotation Invariant Texture Classification

Abstract: This paper presents generalizations to the gray scale and rotation invariant texture classification method based on local binary patterns that we have recently introduced. We derive a generalized presentation that allows for realizing a gray scale and rotation invariant LBP operator for any quantization of the angular space and for any spatial resolution, and present a method for combining multiple operators for multiresolution analysis. The proposed approach is very robust in terms of gray scale variations, since the operator is by definition invariant against any monotonic transformation of the gray scale. Another advantage is computational simplicity, as the operator can be realized with a few operations in a small neighborhood and a lookup table. Excellent experimental results obtained in a true problem of rotation invariance, where the classifier is trained at one particular rotation angle and tested with samples from other rotation angles, demonstrate that good discrimination can be achieved with the occurrence statistics of simple rotation invariant local binary patterns. These operators characterize the spatial configuration of local image texture and the performance can be further improved by combining them with rotation invariant variance measures that characterize the contrast of local image texture. The joint distributions of these orthogonal measures are shown to be very powerful tools for rotation invariant texture analysis.

Edge, junction, and corner detection using color distributions

Abstract: For over 30 years (1970-2000) researchers in computer vision have been proposing new methods for performing low-level vision tasks such as detecting edges and corners. One key element shared by most methods is that they represent local image neighborhoods as constant in color or intensity with deviations modeled as noise. Due to computational considerations that encourage the use of small neighborhoods where this assumption holds, these methods remain popular. The research presented models a neighborhood as a distribution of colors. The goal is to show that the increase in accuracy of this representation translates into higher-quality results for low-level vision tasks on difficult, natural images, especially as neighborhood size increases. We emphasize large neighborhoods because small ones often do not contain enough information. We emphasize color because it subsumes gray scale as an image range and because it is the dominant form of human perception. We discuss distributions in the context of detecting edges, corners, and junctions, and we show results for each.

Data hiding in binary text documents

Abstract: With the proliferation of digital media such as digital images, digital audio, and digital video, robust digital watermarking and data hiding techniques are needed for copyright protection, copy control, annotation, and authentication. While many techniques have been proposed for digital color and grayscale images, not all of them can be directly applied to binary text images. The difficulty lies in the fact that changing pixel values in a binary document could introduce irregularities that are very visually noticeable. We propose a new method for data hiding in binary text documents by embedding data in the 8-connected boundary of a character. We have identified a fixed set of pairs of five-pixel long boundary patterns for embedding data. One of the patterns in a pair requires deletion of the center foreground pixel, whereas the other requires the addition of a foreground pixel. A unique property of the proposed method is that the two patterns in each pair are dual of each other -- changing the pixel value of one pattern at the center position would result in the other. This property allows easy detection of the embedded data without referring to the original document, and without using any special enforcing techniques for detecting embedded data.

Interactive tactile display for computer screen

Abstract: Apparatus for converting a visual image into a tactile image. The apparatus comprises imaging means for converting incident light from the visual image into electrical signals that are proportional to the gray scale intensity of the incident light. The apparatus also comprises a tactile display device having a two-dimensional array of variable height pixels, wherein the height of each pixel in the tactile display is dynamically variable in proportion to the electrical signals from the imaging means. Preferably, the height of each pixel is inversely proportional to the gray scale intensity of the incident light so that the maximum height of a pixel occurs when a corresponding pixel in the visual image is black.

Image editing in the contour domain

Abstract: We propose a novel method for image editing in which the primitive working unit is not a pixel but an edge. The feasibility of this proposal is suggested by the recent work of Elder et al. (1998) showing that a gray-scale image can be accurately represented by its edge map if a suitable edge model and scale selection method are employed. In particular, an efficient algorithm has been reported by Elder et al. (1996) and Elder (1999) to invert such an edge representation to yield a high-fidelity reconstruction of the original image. We combined these algorithms together with an efficient method for contour grouping and an intuitive user interface to allow users to perform image editing operations directly in the contour domain. Experimental results suggest that this novel combination of vision algorithms may increase the efficiency of certain classes of image editing operations.

Locating regions in a target image using color matching, luminance pattern matching and hue plane pattern matching

Abstract: A system and method for locating regions in a target image that match a template image with respect to color and pattern information. The template image is characterized with regard to pattern and color. The method comprises performing a first-pass search using color information from the color characterization of the template image to find one or more color match candidate locations. For each color match candidate location, a luminance, i.e., gray scale, pattern matching search is performed on a region proximal to the location, producing one or more final match regions. For each final match region a hue plane pattern match score may be calculated using pixel samples from the interior of each pattern. A final color match score may be calculated for each final match region. A weighted sum of luminance pattern match, hue pattern match, and color match scores may be calculated, and the scores and sum output.

Content-based characterization of video frame sequences

Abstract: A system and process for video characterization that facilitates video classification and retrieval, as well as motion detection, applications. This involves characterizing a video sequence with a gray scale image having pixel levels that reflect the intensity of motion associated with a corresponding region in the sequence of video frames. The intensity of motion is defined using any of three characterizing processes. Namely, a perceived motion energy spectrum (PMES) characterizing process that represents object-based motion intensity over the sequence of frames, a spatio-temporal entropy (STE) characterizing process that represents the intensity of motion based on color variation at each pixel location, a motion vector angle entropy (MVAE) characterizing process which represents the intensity of motion based on the variation of motion vector angles.

12.1: 12.1′ SVGA Microencapsulated Electrophoretic Active Matrix Display for Information Appliances

Abstract: We describe the successful construction of a 12.1″ 800×600 microencapsulated electrophoretic active matrix display incorporating an a-Si thin film transistor backplane. The display exhibits a print-on-paper-like appearance (high reflectance, high contrast ratio and wide viewing angle) and grayscale at 83 DPI, and demonstrates the material's compatibility with commercial a-Si TFT LCD backplanes.

Pattern projection techniques for volumetric 3D displays and 2D displays

Abstract: This invention relates generally to image projection methods and apparatus for creating color or gray scale images using spatial light modulators (SLMs) without color or gray capability. The basic concept is to divide the pixels on a single SLM into multiple groups and then illuminate each group with a different primary color. The content of the single SLM panel can then be programmed as if there are multiple sub-panels illuminated with different primary colors. The combined image on the single panel therefore displays images of many colors. Illumination can be achieved by projection of a pattern of color or gray scale distribution to the surface of the SLM panel and registering the pattern to corresponding pixel groups; or can be implemented by applying a proximity pattern close to the SLM surface. This technique can be applied to volumetric 3D displays, 2D displays, and optical correlators.

Adaptive threshold modulation for error diffusion halftoning

Abstract: Grayscale digital image halftoning quantizes each pixel to one bit. In error diffusion halftoning, the quantization error at each pixel is filtered and fed back to the input in order to diffuse the quantization error among the neighboring grayscale pixels. Error diffusion introduces nonlinear distortion (directional artifacts), linear distortion (sharpening), and additive noise. Threshold modulation, which alters the quantizer input, has been previously used to reduce either directional artifacts or linear distortion. This paper presents an adaptive threshold modulation framework to improve halftone quality by optimizing error diffusion parameters in the least squares sense. The framework models the quantizer implicitly, so a wide variety of quantizers may be used. Based on the framework, we derive adaptive algorithms to optimize 1) edge enhancement halftoning and 2) green noise halftoning. In edge enhancement halftoning, we minimize linear distortion by controlling the sharpening control parameter. We may also break up directional artifacts by replacing the thresholding quantizer with a deterministic bit flipping (DBF) quantizer. For green noise halftoning, we optimize the hysteresis coefficients.

Improved techniques for automatic image segmentation

Abstract: Mathematical morphology is very attractive for automatic image segmentation because it efficiently deals with geometrical descriptions such as size, area, shape, or connectivity that can be considered as segmentation-oriented features. This paper presents an image-segmentation system based on some well-known strategies. The segmentation process is divided into three basic steps, namely: simplification, marker extraction, and boundary decision. Simplification, which makes use of area morphology, removes unnecessary information from the image to make it easy to segment. Marker extraction identifies the presence of homogeneous regions. A new marker extraction design is proposed in this paper. It is based on both luminance and color information. The goal of boundary decision is to precisely locate the boundary of regions detected by the marker extraction. This decision is based on a region-growing algorithm which is a modified watershed algorithm. A new color distance is also defined for this algorithm. In both marker extraction and boundary decision, color measurement is used to replace grayscale measurement and L*a*b* color space is used to replace the more straightforward spaces such as the RGB color space and YUV color space.

Affine-invariant recognition of gray-scale characters using global affine transformation correlation

Abstract: Describes a technique of gray-scale character recognition that offers both noise tolerance and affine-invariance. The key ideas are twofold. First is the use of normalized cross-correlation as a matching measure to realize noise tolerance. Second is the application of global affine transformation (GAT) to the input image so as to achieve affine-invariant correlation with the target image. In particular, optimal GAT is efficiently determined by the successive iteration method using topographic features of gray-scale images as matching constraints. We demonstrate the high matching ability of the proposed GAT correlation method using gray-scale images of numerals subjected to random Gaussian noise and a wide range of affine transformation. Moreover, extensive recognition experiments show that the achieved recognition rate of 94.3 percent against rotation within 30 degrees, scale change within 30 percent, and translation within 20 percent of the character width along with random Gaussian noise is sufficiently high compared to the 42.8 percent offered by simple correlation.

The science of digitizing paintings for color-accurate image archives: a review

Abstract: A review of the human visual system, the CIE L * , a * , b * color space and its use in evaluating color image quality, and digital image capture is presented, the goal of which is to provide background information for imaging professionals involved in creating digital image databases for museums, galleries, archives, and libraries. Following this review, an analysis was performed to determine the effects of bit depth, dynamic range, gamma correction, and color correction on the ability to estimate colorimetric data from R, G, B digital images with a minimum of error. The proper use of gray scale and color targets was also considered. Recommendations are presented for the direct digital image capture of paintings. Finally, a brief look into the future using spectral imaging techniques is presented.

Topological operators for grayscale image processing

Abstract: In a recent work, we introduced some topological notions for grayscale images based on a cross-section topology. In particular, the notion of destructible point, which corresponds to the classical notion of simple point, allows us to build operators that simplify a grayscale image while preserving its topology. In this paper, we introduce new notions and operators in the framework of the cross-section topology. In particular, the notion of -destructible point allows us to selectively modify the topology, based on a local contrast parameter . By combining homotopic and non-homotopic operators, we introduce new methods for ltering, thinning, segmenting and enhancing grayscale image.

Apparatus and method for halftone hybrid screen generation

Abstract: The present invention is a method and apparatus allowing the application of two or more distinct halftone types in the rendering of a single image. The invention employs a halftone selector of a threshold type, or as an alternative a segmenter type. The halftone selector determines which areas of an image will receive which type of grayscale halftone treatment on a pixel by pixel basis. Examples of various halftone types include stochastic, clustered dot, line screen, and other high addressability types. Each pixel of data is treated by the appropriate halftoner circuit which in response outputs digital data. A controller circuit remaps the digital data into the appropriate width and position signals for a pulse width position modulator, including any other signals as needed for any additional inverter circuitry. The pulse width position modulator generates a video signal which may be inverted by the inverter circuit as responsive to the controller circuit remapping determination. This final video signal is provided to an image output terminal.

Design of connected operators using the image foresting transform

Abstract: The Image Foresting Transform (IFT) reduces optimal image partition problems from seed pixels into a shortest-path forest problem in a graph, whose solution can be obtained in linear time It has allowed a unified and efficient approach to edge tracking, region growing, watershed transforms, multiscale skeletonization, and Euclidean distance transform In this paper, we extend the IFT to introduce two connected operators: cutting-off-domes and filling-up-basins The former simplifies grayscale images by reducing the height of its domes, while the latter reduces the depth of its basins By automatically or interactively specifying seed pixels in the image and computing a shortest-path forest, whose trees are rooted at these seeds, the IFT creates a simplified image where the brightness of each pixel is associated with the length of the corresponding shortest-path A label assigned to each seed is propagated, resulting a labeled image that corresponds to the watershed partitioning from markers The proposed operators may also be used to provide regional image filtering and labeling of connected components We combine the cutting-off-domes and filling-up-basins to implement regional minima/maxima, h-domes/basins, opening/closing by reconstruction, leveling, area opening/closing, closing of holes, and removal of pikes Their applications are illustrated with respect to medical image segmentation

Wavelet-based space-frequency compression of ultrasound images

Abstract: This paper describes the compression of grayscale medical ultrasound images using a recent compression technique, i.e., space-frequency segmentation (SITS). This method finds the rate-distortion optimal representation of an image from a large set of possible space-frequency partitions and quantizer combinations and is especially effective when the images to code are statistically inhomogeneous, which is the case for medical ultrasound images. We implemented a compression application based on this method and tested the algorithm on representative ultrasound images. The result is an effective technique that performs better than a leading wavelet-transform coding algorithm, i.e., set partitioning in hierarchical trees (SPIHT), using standard objective distortion measures. To determine the subjective qualitative performance, an expert viewer study was run by presenting ultrasound radiologists with images compressed using both SFS and SPIHT. The results confirmed the objective performance rankings. Finally, the performance sensitivity of the space-frequency codec is shown with respect to several parameters, and the characteristic space-frequency partitions found for ultrasound images are discussed.

Method for extracting titles from digital images

Abstract: A method of delineating titles within a grayscale image, in which a grayscale image is received, e.g., by scanning a document, and then is subjected to multi-level thresholding to obtain a plurality of binary images representing the original grayscale image. Each of the binary images is preferably pre-processed to filter any noise components from each of the binary images, and then all connected components within each of said binary images are identified, optionally filtered, and then clustered to identify possible title regions within each of the binary images. Next, each binary image is preferably post-processed to merge possible title regions comprising strokes and to remove non-title regions from the previously identified possible title regions in each of the images by comparing characteristics of the previously identified possible title regions to pre-determined criteria. Further, certain of the previously identified possible title regions within each of the binary images which satisfy pre-determined criteria are merged together. Still further, title regions within each of the binary images are combined after the post-processing step and the merging step. Finally, certain of the previously identified possible title regions for different layers are preferably merged to identify all possible title regions. Once the title region are located, various processing can be performed to extract the text from the title region.

Environment-compliant image display system and program

Abstract: To provide an environment-compliant image display system and program, there is provided a color control processing update section which corrects colors by adjusting a LUT in a 3D-LUT storage section and corrects brightness by adjusting γ values in a 1D-LUT storage section, to increase an output value in at least a lower grayscale range when the environment is affected by ambient light, based on environmental information that has been obtained by a colored-light sensor.

Similarity templates for detection and recognition

Abstract: This paper investigates applications of a new representation for images, the similarity template. A similarity template is a probabilistic representation of the similarity of pixels in an image patch. It has application to detection of a class of objects, because it is reasonably invariant to the color of a particular object. Further, it enables the decomposition of a class of objects into component parts over which robust statistics of color can be approximated. These regions can be used to create a factored color model that is useful for recognition. Detection results are shown on a system that learns to detect a class of objects (pedestrians) in static scenes based on examples of the object provided automatically by a tracking system. Applications of the factored color model to image indexing and anomaly detection are pursued on a database of images of pedestrians.

Grayscale image connected components segmentation

Abstract: A method and system of reading images The method includes decimating an image and normalizing the decimated image Then, rebinning grayscale pixel data associated with the decimated image and reassigning a selected range of grayscales representing a region of interest of the remapped grayscale pixel data to one while zeroing others The method also includes labeling the connected pixels associated with the range of grayscales representing the region of interest and then extending the connected pixels through region growing using a preselected offset value Lastly, the method includes filtering segmented regions of the connected pixels to eliminate certain candidates The system is designed to implement the steps of the enumerated method

Fast fractal compression of greyscale images

Abstract: A new algorithm for fractal compression of greyscale images is presented. It uses some previous results allowing the compression process to be reduced to a nearest neighbors problem, and is essentially based on a geometrical partition of the image block feature space. Experimental comparisons with previously published methods show a significant improvement in speed with no quality loss.

A pseudo-distance map for the segmentation-free skeletonization of gray-scale images

Abstract: In this paper we introduce a new tool, called a pseudo-distance map (PDM), for extracting skeletons from grayscale images without region segmentation or edge detection. Given an edge-strength function (ESF) of a gray-scale image, the PDM is computed from the ESF using the partial differential equations we propose. The PDM can be thought of as a relaxed version of a Euclidean distance map. Therefore, its ridges correspond to the skeleton of the original gray-scale image and it provides information on the approximate width of skeletonized structures. Since the PDM is directly computed from the ESF without thresholding it, the skeletonization result is generally robust and less noisy. We tested our method using a variety of synthetic and real images. The experimental results show that our method works well on such images.

Increasing Brightness in Field-Sequential Color Displays

Abstract: A display system includes a display panel having an array of pixels, the pixels having ON states and OFF states. The pixels form images by modulating light in a temporal sequence during an image frame in response to drive signals generated from incoming video data. A light source arrangement that emits at least two colors of light illuminates the display panel. The image frame is divided into color segments with only one color of light being emitted from the light source during each segment. The color segments are further divided into grayscale periods. Transition segments are provided for the transitions between colors. The state of each pixel during these transition segments is a function of the desired brightness level for each pixel, as derived from incoming video data.

Image processing device and image processing method

Abstract: Disclosed are an image processing device and an image processing method capable of generating a high-resolution color image of a fine gray scale from image data of a small information amount by using a small memory capacity A character graphics image of high resolution generated by a character rasterizing block is converted by a conversion block to image data in which color information of one color is assigned per group of pixels, and tag information indicating whether the color information is used or not is added with respect to the multiple pixels to which the color information is assigned By the tag information, while maintaining the high resolution, a fine gray scale can be assured An image decoding block which has received such image data decodes the image data into a color image of output resolution by assigning the color information to the position indicated by the tag information For example, the color of peripheral pixels may be assigned to a pixel to which no color information is assigned by the tag information