Automatic tracing of vocal-fold motion from high-speed digital images

Defining characteristics of the phonatory vocal fold vibration is essential for studies that aim to understand the mechanism of voice production and for clinical diagnosis of voice disorders. The application of high-speed digital imaging techniques to these studies makes it possible to capture sequences of images of the vibrating vocal folds at a frequency that can resolve the actual vocal fold vibrations of a patient. The objective of this study is to introduce a new approach for automatic tracing of vocal fold motion from image sequences acquired from high-speed digital imaging of the larynx. The approach involves three process steps. 1) Global thresholding--the threshold value is selected on the basis of the histogram of the image, which is assumed to follow Rayleigh distribution; 2) applying a morphology operator to remove the isolated object regions; 3) using region-growing to delineate the object, or the vocal fold opening region, and to obtain the area of the glottis; the segmented object obtained after global threshold and the morphological operation is used as a seed region for the final region-growing operation. The performance, effectiveness and validation of our approach is demonstrated using representative, high-speed imaging recordings of subjects having normal and pathological voices.     

Evolution of digital images

The ability to create art is a uniquely human endeavor. Throughout history, humans have used paintings, drawings, songs, stories, and other art forms to communicate important ideas or events and to entertain. The advent of computers gave rise to a new medium for art. Computer generated art work has become popular in the entertainment and education industries. The paper uses genetic algorithms (GAs) to automatically evolve a set of unique digital images according to a predetermined set of criteria. By monitoring and automatically evaluating geometric features in images, the work reported in the paper intends to evolve interesting images with a variety of geometric features without the need for human intervention.     

Automatic assessment of macular edema from color retinal images

Diabetic macular edema (DME) is an advanced symptom of diabetic retinopathy and can lead to irreversible vision loss. In this paper, a two-stage methodology for the detection and classification of DME severity from color fundus images is proposed. DME detection is carried out via a supervised learning approach using the normal fundus images. A feature extraction technique is introduced to capture the global characteristics of the fundus images and discriminate the normal from DME images. Disease severity is assessed using a rotational asymmetry metric by examining the symmetry of macular region. The performance of the proposed methodology and features are evaluated against several publicly available datasets. The detection performance has a sensitivity of 100% with specificity between 74% and 90%. Cases needing immediate referral are detected with a sensitivity of 100% and specificity of 97%. The severity classification accuracy is 81% for the moderate case and 100% for severe cases. These results establish the effectiveness of the proposed solution.     

Nonlinear estimation of scene parameters from digital images usingzero-hit-length statistics

A zero-hit run-length probability model for image statistics is derived. The statistics are based on the lengths of runs of pixels that do not include any part of objects that define a scene model. The statistics are used to estimate the density and size of the discrete objects (modeled as disks) from images when the image pixel size is significant relative to the object size. Using different combinations of disk size, density, and image resolution (pixel size) in simulated images, parameter estimation may be used to investigate the essential invertibility of object size and density. Analysis of the relative errors and 95% confidence intervals indicates the accuracy and reliability of the estimates. An integrated parameter r, reveals relationships between errors and the combinations of the three basic parameters of object size, density, and pixel size. The method may be used to analyze real remotely sensed images if simplifying assumptions are relaxed to include the greater complexity found in real data     

Hidden digital watermarks in images

An image authentication technique by embedding digital "watermarks" into images is proposed. Watermarking is a technique for labeling digital pictures by hiding secret information into the images. Sophisticated watermark embedding is a potential method to discourage unauthorized copying or attest the origin of the images. In our approach, we embed the watermarks with visually recognizable patterns into the images by selectively modifying the middle-frequency parts of the image. Several variations of the proposed method are addressed. The experimental results show that the proposed technique successfully survives image processing operations, image cropping, and the Joint Photographic Experts Group (JPEG) lossy compression.     

Colorimetric restoration of digital images

A colorimetric approach to restoration of digital images is presented. Assumptions are made to simplify the general problem to obtain a more computable form. Two methods are developed, using Karhunen-Loeve transformation and independent restoration schemes from earlier works, to solve the estimation problem in color image processing using multidimensional restoration. A comparison of the methods is presented including the effects of parameters of interest to desktop scanners and digital cameras. The results for the SNRs and blurs studied indicate that more than three color channels produces a slight numerical gain and modest visual gain.     

Identification of inpainted images and natural images for digital forensics

Image forensics is a form of image analysis for finding out the condition of an image in the complete absence of any digital watermark or signature.It can be used to authenticate digital images and identify their sources.While the technology of exemplar-based inpainting provides an approach to remove objects from an image and play visual tricks.In this paper,as a first attempt,a method based on zero-connectivity feature and fuzzy membership is proposed to discriminate natural images from inpainted images.Firstly,zero-connectivity labeling is applied on block pairs to yield matching degree feature of all blocks in the region of suspicious,then the fuzzy memberships are computed and the tampered regions are identified by a cut set.Experimental results demonstrate the effectiveness of our method in detecting inpainted images.     

A thinning transform for digital images

Given an elongated object in a digital image, a thinning transform is described to simultaneously calculate the coordinates of its medial line elements and a value for these elements equal to the width of the object at the element's coordinates. The transform is being used in the area of quantitative fractography in photo-micrographs of rock samples.     

Measuring perceptual contrast in digital images

In this paper we present a novel method to measure perceptual contrast in digital images. We start from a previous measure of contrast developed by Rizzi et al. [26], which presents a multilevel analysis. In the first part of the work the study is aimed mainly at investigating the contribution of the chromatic channels and whether a more complex neighborhood calculation can improve this previous measure of contrast. Following this, we analyze in detail the contribution of each level developing a weighted multilevel framework. Finally, we perform an investigation of Regions-of-Interest in combination with our measure of contrast. In order to evaluate the performance of our approach, we have carried out a psychophysical experiment in a controlled environment and performed extensive statistical tests. Results show an improvement in correlation between measured contrast and observers perceived contrast when the variance of the three color channels separately is used as weighting parameters for local contrast maps. Using Regions-of-Interest as weighting maps does not improve the ability of contrast measures to predict perceived contrast in digital images. This suggests that Regions-of-Interest cannot be used to improve contrast measures, as contrast is an intrinsic factor and it is judged by the global impression of the image. This indicates that further work on contrast measures should account for the global impression of the image while preserving the local information.     

数字图像水印研究综述

本文对当前数字图像水印技术的背景、现有方法、发展应用和存在的问题做了一综述,以期进一步推动我国在此前沿领域的研究工作。     

Watermarking digital images for copyright protection

A watermark is an invisible mark placed on an image that is designed to identify both the source of an image as well as its intended recipient. The authors present an overview of watermarking techniques and demonstrate a solution to one of the key problems in image watermarking, namely how to hide robust invisible labels inside grey scale or colour digital images     

BTC-VQ-DCT hybrid coding of digital images

A hybrid BTC-VQ-DCT (block truncation coding, vector quantization, and discrete cosine transform) image coding algorithm is presented. The algorithm combines the simple computation and edge preservation properties of BTC and the high fidelity and high-compression ratio of adaptive DCT with the high-compression ratio and good subjective performance of VQ, and can be implemented with significantly lower coding delays than either VQ or DCT alone. The bit-map generated by BTC is decomposed into a set of vectors which are vector quantized. Since the space of the BTC bit-map is much smaller than that of the original 8-b image, a lookup-table-based VQ encoder has been designed to `fast encode' the bit-map. Adaptive DCT coding using residual error feedback is implemented to encode the high-mean and low-mean subimages. The overall computational complexity of BTC-VQ-DCT coding is much less than either DCT and VQ, while the fidelity performance is competitive. The algorithm has strong edge-preserving ability because of the implementation of BTC as a precompress decimation. The total compression ratio is about 10:1     

Dynamic finite-state vector quantization of digital images

A vector quantization (VQ) scheme with finite memory called dynamic finite-state vector quantization (DFSVQ) is presented. The encoder consists of a large codebook, so called super-codebook, where for each input vector a fixed number of its codevectors are chosen to generate a much smaller codebook (sub-codebook). This sub-codebook represents the best matching codevectors that could be found in the super-codebook for encoding the current input vector. The choice for the codevectors in the sub-codebook is based on the information obtained from the previously encoded blocks where directional conditional block probability (histogram) matrices are used in the selection of the codevectors. The index of the best matching codevector in the sub-codebook is transmitted to the receiver. An adaptive DFSVQ scheme is also proposed in which, when encoding an input vector, first the sub-codebook is searched for a matching codevector to satisfy a pre-specified waveform distortion. If such a codevector is not found in tile current sub-codebook then the whole super-codebook is checked for a better match. If a better match is found then a signaling flag along with the corresponding index of the codevector is transmitted to the receiver. Both the DFSVQ encoder and its adaptive version are implemented. Experimental results for several monochrome images with a super-codebook size of 256 or 512 and different sub-codebook sizes are presented     

Perceptual watermarks for digital images and video

The growth of new imaging technologies has created a need for techniques that can be used for copyright protection of digital images and video. One approach for copyright protection is to introduce an invisible signal, known as a digital watermark, into an image or video sequence. In this paper, we describe digital watermarking techniques, known as perceptually based watermarks, that are designed to exploit aspects of the the human visual system in order to provide a transparent (invisible), yet robust watermark. In the most general sense, any watermarking technique that attempts to incorporate an invisible mark into an image is perceptually based. However, in order to provide transparency and robustness to attack, two conflicting requirements from a signal processing perspective, more sophisticated use of perceptual information in the watermarking process is required. We describe watermarking techniques ranging from simple schemes which incorporate common-sense rules in using perceptual information in the watermarking process, to more elaborate schemes which adapt to local image characteristics based on more formal perceptual models. This review is not meant to be exhaustive; its aim is to provide the reader with an understanding of how the techniques have been evolving as the requirements and applications become better defined     

A robust method for fingerprinting digital images

In this paper, a method to fingerprint digital images is proposed, and different watermarked copies with different identification string are made. After determining the number of the customers and the length of the watermark string, this method chooses some values inside the digital image using a characteristic function, and adds watermarks to these values in a way that can protect the product against the attacks happened by comparing two fingerprinted copies. The watermarks are a string of binary numbers -1s and 1s. Every customer will be distinguished by a series of 1s and -1s generated by a pseudo-random generator. The owner of the image can determine the number of customers and the length of the string as well as this method will add another watermarking values to watermark string to protect the product.     

灰度图像水印综述

数字水印技术作为数字媒体版权保护的重要手段之一,近年来已成为国内外研究的热点.与传统的嵌入一个无意义的一维或二维伪随机序列以及可视的二值图像相比,嵌入灰度图像水印不仅嵌入信息量大,而且更加有意义.对灰度级数字图像水印技术的最新发展情况进行了介绍,主要内容包括:空域及变换域的灰度数字图像水印技术,其中变换域水印主要讨论了DCF域和DWT域两类灰度数字水印;自适应灰度级数字水印技术;灰度数字图像水印的性能评价.最后展望了该技术的进一步研究前景及可能的研究热点.     

Authentication and correction of digital watermarking images

A novel function for image watermarking is introduced. The proposed function gives a restoration/correction capability to image watermarking as well as the detection and localisation of alterations. The basic idea of the proposed watermarking technique is to adopt conventional error control coding techniques for generating a watermark.     

CCD noise removal in digital images.

In this work, we propose a denoising scheme to restore images degraded by CCD noise. The CCD noise model, measured in the space of incident light values (light space), is a combination of signal-independent and signal-dependent noise terms. This model becomes more complex in image brightness space (normal camera output) due to the nonlinearity of the camera response function that transforms incoming data from light space to image space. We develop two adaptive restoration techniques, both accounting for this nonlinearity. One operates in light space, where the relationship between the incident light and light space values is linear, while the second method uses the transformed noise model to operate in image space. Both techniques apply multiple adaptive filters and merge their outputs to give the final restored image. Experimental results suggest that light space denoising is more efficient, since it enables the design of a simpler filter implementation. Results are given for real images with synthetic noise added, and for images with real noise.     

Authenticity and integrity of digital mammography images

Data security becomes more and more important in telemammography which uses a public high-speed wide area network connecting the examination site with the mammography expert center. Generally, security is characterized in terms of privacy, authenticity and integrity of digital data. Privacy is a network access issue and is not considered in this paper. We present a method, authenticity and integrity of digital mammography, here which can meet the requirements of authenticity and integrity for mammography image (IM) transmission. The authenticity and integrity for mammography (AIDM) consists of the following four modules. 1) Image preprocessing: To segment breast pixels from background and extract patient information from digital imaging and communication in medicine (DICOM) image header. 2) Image hashing: To compute an image hash value of the mammogram using the MD5 hash algorithm. 3) Data encryption: To produce a digital envelope containing the encrypted image hash value (digital signature) and corresponding patient information. 4) Data embedding: To embed the digital envelope into the image. This is done by replacing the least significant bit of a random pixel of the mammogram by one bit of the digital envelope bit stream and repeating for all bits in the bit stream. Experiments with digital IMs demonstrate the following. 1) In the expert center, only the user who knows the private key can open the digital envelope and read the patient information data and the digital signature of the mammogram transmitted from the examination site. 2) Data integrity can be verified by matching the image hash value decrypted from the digital signature with that computed from the transmitted image. 3) No visual quality degradation is detected in the embedded image compared with the original. Our preliminary results demonstrate that AIDM is an effective method for image authenticity and integrity in telemammography application.