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detection of textured areas in natural images using an indicator based on component counts

JOURNAL OF ELECTRONIC IMAGING 2008年第4期17卷 043003-043003-13页

作者： Bergman, Ruth Nachlieli, Hila Ruckenstein, Gitit Hewlett Packard Corp IL-32000 Technion Haifa Israel

An algorithm is presented for the detection of textured areas in natural images. Texture detection has potential application to image enhancement, tone correction, defect detection, content classification, and image segmentation. For example, texture detection may be useful for object detection when combined with color models and other descriptors. Sky, e.g., is generally smooth, and foliage is textured. The texture detector presented here is based on the intuition that texture in a natural image is comprised of many components. The measure we develop examines the structure of local regions of the image. This structural approach enables us to detect both structured and unstructured textures at many scales. Furthermore, it distinguishes between edges and texture, and also between texture and noise. Automatic detection results are shown to match human classification of corresponding image areas. (C) 2008 SPIE and IS&T [DOI: 10.1117/1.2981836]

关键词： Denoising detection and tracking algorithms Image enhancement Sensors algorithms Signal processing Image segmentation

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Morphological characterization of dithering masks

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JOURNAL OF ELECTRONIC IMAGING 2003年第2期12卷 278-283页

作者： Misic, V Parker, KJ Univ Rochester Dept Elect & Comp Engn Rochester NY 14627 USA

We present some novel tools for the analysis of blue-noise binary patterns. Unlike most of the existing methods that evaluate the frequency content of a given mask or its lower order statistics, our new metrics characterize the morphological content of a mask that is quantified using simple one-pass filtering. An analytical filter expression is given. As a result, one can balance the structural content of the mask-diagonal, vertical, and horizontal interconnections of the majority (or minority) pixels-at the same level. In addition, it is possible to improve the overall mask quality by prescribing the occurrence of morphological shapes of connected pixels. Examples of morphological analysis are given to demonstrate the different qualities of blue-noise and white-noise patterns. (C) 2003 SPIE and IST.

关键词： Binary data Halftones Image filtering Visualization Convolution detection and tracking algorithms Digital filtering Morphological analysis Statistical analysis Visual system

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DESIGN OF IMAGE-ADAPTIVE QUANTIZATION TABLES FOR JPEG

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JOURNAL OF ELECTRONIC IMAGING 1995年第2期4卷 144-150页

作者： FUNG, HT PARKER, KJ Univ. of Rochester (United States)

The rate-distortion trade-off in the discrete cosine transform-based coding scheme in ISO/JPEG is determined by the quantization table. To permit a different quality to be selected by a user, a common practice is to scale the standard quantization tables that have been empirically determined from psychovisual experiments. In this paper, an algorithm is presented to generate a quantization table that is optimized for a given image and for a given distortion. The computational complexity of this algorithm is reduced compared to other techniques. The optimized, image-adaptive quantization table typically yields an improvement of 15% to 20% in bit rate compared to the use of standard, scaled quantization tables. Once an optimized quantization table has been generated for a specific image, it can also be applied to other images with similar content with a small sacrifice in bit rate.

关键词： Quantization Distortion detection and tracking algorithms Image compression Computer programming Image enhancement Image quality Error analysis Signal to noise ratio Yield improvement

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Adaptive error diffusion algorithm incorporating a visual model

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JOURNAL OF ELECTRONIC IMAGING 1998年第3期7卷 655-663页

作者： Spaulding, KE Couwenhoven, DW Miller, RL Eastman Kodak Co Imaging Res & Adv Dev Rochester NY 14650 USA

This paper describes an improved error diffusion algorithm for the purpose of digitally halftoning images. In one variation of the algorithm an error signal is calculated by the difference between a visually perceived input value and a visually perceived output value. This is accomplished by applying a causal visual blur function to both the input and output images. This approach has the advantage that it minimizes the appearance of worm artifacts in the output image, while simultaneously eliminating the edge artifacts associated with a previous visual error diffusion algorithm. In a second variation of the improved error diffusion algorithm, a local image activity detector is used to adaptively modify the input and output blur filters. This allows the error diffusion parameters to be optimized for different types of image content. (C) 1998 SPIE and IS&T. [S1017-9909(98)01903-5].

关键词： Visualization Diffusion Image filtering Digital filtering Electronic filtering Convolution Sensors detection and tracking algorithms Image processing Error analysis

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Nearest-neighbor and bilinear resampling factor estimation to detect blockiness or blurriness of an image

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JOURNAL OF ELECTRONIC IMAGING 2008年第2期17卷 023005-023005-16页

作者： Suwendi, Ariawan Allebach, Jan P. Xerox Corp Webster NY 14580 USA Purdue Univ W Lafayette IN 47907 USA

In digital publishing, a low-resolution image is highly undesirable. Inexperienced users often try to include low-resolution images from the Internet or digital cameras in documents they are composing. Current preflight tools are able to single them out, but what if those low-resolution images have been interpolated? They may have a sufficient resolution, but their quality has been compromised, especially images interpolated by nearest-neighbor (which includes pixel replication) and bilinear interpolation. The interpolated images often display blocky artifacts, blurry artifacts, or loss of texture. We outline novel nearest-neighbor and bilinear interpolation detection algorithms that are designed to estimate rational resampling factors (above 1 X) in both the vertical and horizontal dimensions. The robustness of these algorithms to several common post-processing algorithms is also evaluated. (C) 2008 SPIE and IS&T.

关键词： algorithms detection and tracking algorithms Digital watermarking

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Computational approach for edge linking

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JOURNAL OF ELECTRONIC IMAGING 2002年第4期11卷 479-485页

作者： Ghita, O Whelan, PF Dublin City Univ Sch Elect Engn Vis Syst Lab Dublin 9 Ireland

Efficient edge operators such as those based on partial derivatives fail to return continuous edge maps. To address this, a supplementary edge linking step is required to complete initial edge information. In this paper we. propose a fast and efficient algorithm for edge linking using local information around edge terminators. In order to minimize incorrect linking decisions, the direction and the linking path for each edge terminator are established by minimizing a cost function. The particular novelty of this approach lies in the labeling scheme which assigns the directionality of the. edge terminators (endpoints) based only on local knowledge. As a consequence, it relaxes the demand of a priori knowledge and furthermore assures an accurate and efficient search for edge paths in the image. (C) 2002 SPIE and IST.

关键词： detection and tracking algorithms Edge detection Sensors Image processing Image restoration Image segmentation Algorithm development Image analysis Image processing algorithms and systems Image resolution

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FLIR ATR using location uncertainty

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JOURNAL OF ELECTRONIC IMAGING 2000年第2期9卷 178-193页

作者： Liu, G Haralick, RM Univ Washington Dept Elect Engn Intelligent Syst Lab Seattle WA 98195 USA

A model-based FLIR ATR algorithm is described. It utilizes boundary contrast for target detection and recognition. Boundary contrast is related to the location uncertainty at target boundary points. A polygon model is used for deriving target centroid location uncertainty caused by the boundary point location uncertainty. The significance of the work lies in the sound mathematical models used in deriving the relationship between contrast and location uncertainty for the boundary points and the relationship between boundary point location uncertainty and centroid location uncertainty Experiment results show significantly improved performance in detection, recognition, and localization. (C) 2000 SPIE and IS&T. [S1017-9909(00)01602-0].

关键词： detection and tracking algorithms Forward looking infrared Automatic target recognition Target detection Target recognition Signal to noise ratio Image segmentation Algorithm development Error analysis Sensors

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Multigradient field-active contour model for multilayer boundary detection of ultrasound rectal wall image

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JOURNAL OF ELECTRONIC IMAGING 2005年第3期14卷 033010.1-033010.1页

作者： Xiao, D Ng, WS Aheyratne, UR Tsang, CB Natl Univ Singapore Hosp Dept Surg Singapore 169608 Singapore Nanyang Technol Univ Sch Mech & Prod Engn Comp Integrated & Med Intervent Lab Singapore 639798 Singapore Univ Queensland Sch Info Tech & Elect Eng Brisbane Qld 4072 Australia

Extraction and reconstruction of rectal wall structures from an ultrasound image is helpful for surgeons in rectal clinical diagnosis and 3-D reconstruction of rectal structures from ultrasound images. The primary task is to extract the boundary of the muscular layers on the rectal wall. However, due to the low SNR from ultrasound imaging and the thin muscular layer structure of the rectum, this boundary detection task remains a challenge. An active contour model is an effective high-level model, which has been used successfully to aid the tasks of object representation and recognition in many image-processing applications. We present a novel multigradient field active contour algorithm with an extended ability for multiple-object detection, which overcomes some limitations of ordinary active contour models-"snakes." The core part in the algorithm is the proposal of multigradient vector fields, which are used to replace image forces in kinetic function for alternative constraints on the deformation of active contour, thereby partially solving the initialization limitation of active contour for rectal wall boundary detection. An adaptive expanding force is also added to the model to help the active contour go through the homogenous region in the image. The efficacy of the model is explained and tested on the boundary detection of a ring-shaped image, a synthetic image, and an ultrasound image. The experimental results show that the proposed multigradient field-active contour is feasible for multilayer boundary detection of rectal wall. (c) 2005 SPIE and IS&T

关键词： Ultrasonography detection and tracking algorithms Rectum Tumors Image processing Surgery 3D image processing 3D image reconstruction Improvised explosive devices Object recognition

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Learning object models from graph templates

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JOURNAL OF ELECTRONIC IMAGING 1997年第3期6卷 294-302页

作者： Mirhosseini, AR Yan, H Univ Sydney Dept Elect Engn Sydney NSW 2006 Australia

This paper describes a novel neural network (NN) based system for defecting rigid objects from their (2-D) gray-level image images. In this approach a labeled graph is employed to construct a template model for an object from the image region where the object is located A novel network of NN (NoNN) is proposed to learn the examples of object model graph templates. The NoNN is composed of a set of subnetworks that are not connected to one another The selected network topology improves the generalization of the classifier in terms of its Vapnik-Chervonenkis dimension (VCdim). Each subnetwork is a network of multilayer perception neural network classifiers operating in parallel with the rest of the system. Each subnetwork is assigned to learn the label of one vertex of a graph, The detection scheme combines the decisions of the subnetworks to classify an image graph extracted from an input image block. This visual computational model is potentially useful for partial matching where the object is occluded. Performance of the system is tested in modeling and detection of human eye regions in face images with some degree of variation in the direction of pose;(C) 1997 SPIE and IS&T.

关键词： Eye models Eye Wavelets Feature extraction detection and tracking algorithms Neural networks Image analysis Image processing Visualization Systems modeling

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Efficiently tracking a moving object in two-dimensional image space

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JOURNAL OF ELECTRONIC IMAGING 2001年第3期10卷 785-793页

作者： Barrett, SF Wright, CHG Zwick, H Wilcox, M Rockwell, BA Naess, E Univ Wyoming Dept Elect Engn Laramie WY 82071 USA USAF Acad Dept Elect Engn Colorado Springs CO 80840 USA USA Res Detachment Walter Reed Army Inst Res Brooks AFB TX 78235 USA USAF Acad Dept Biol Colorado Springs CO 80840 USA USAF Human Effectiveness Directorate Opt Radiat Branch Brooks AFB TX 78235 USA

A tracking algorithm has been developed to efficiently track a moving object in two-dimensional image space. The algorithm employs a limited exhaustive template matching scheme that combines the accuracy of an exhaustive search with the computational efficiency of a coarse-fine template matching scheme, The overall result is an accurate, time-efficient tracking algorithm. After providing a theoretical discussion of the algorithm, three separate biomedical applications of the algorithm are described. (1) stabilizing an irradiating laser on the retinal surface for photocoagulation treatment, (2) measuring target fixation eye movement to construct pattern densities at the retina, and (3) tracking a rat swimming in a Morris Water Maze for psychophysiological studies. Results for each application is provided, The paper concludes Vith a discussion of the relative merits of the tracking algorithm and recommendations for methods to improve the performance of the algorithm. (C) 2001 SPIE and IS&T.

关键词： detection and tracking algorithms Retina Algorithm development Video Eye Head Cameras Laser coagulation Scanning laser ophthalmoscopy Electrical engineering

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