Suppose a dispersed-dot dither matrix is treated as a collection of numbers, each number having a position in space; when the numbers are visited in increasing order, what is the distance in space between pairs of consecutive numbers visited? In Bayer’s matrices, this distance is always large. We hypothesize that this large consecutive distance is important for good dispersed-dot threshold matrices. To study the hypothesis, matrices that have this quality were generated by solving a more general problem: given an arbitrary set of points on the plane, sort them into a list where consecutive points are far apart. Our solution colors the nearestneighbor graph, hierarchically. The method does reproduce Bayer’s dispersed-dot dither matrices under some settings and, furthermore, can produce matrices of arbitrary dimensions. Multiple similar matrices can be created to minimize repetitive artifacts that plague Bayer dither while retaining its parallelizability. The method can also be used for halftoning with points on a hexagonal grid, or even randomly placed points. It can also be applied to artistic dithering, which creates a dither matrix from a motif image. Unlike in the artistic dither method of Ostromoukhov and Hersch, the motif image can be arbitrary and need not be specially constructed.

This is a generalization, to color images, of earlier results on two-dimensional monochromatic halftoning with error diffusion neural networks (EDNs). Previously, we have shown that EDNs find local minima of frequency-weighted error between a binary halftone output and corresponding smoothly varying input, which is an ideal framework for solving halftone problems. We cast color halftoning as four related subproblems: the first three are to compute good binary halftones for each primary color and the fourth is to simultaneously minimize frequency-weighted error in the luminosity of the composite result. We show that an EDN with a three-dimensional (3D) interconnection scheme can solve all four problems in parallel. The 3D EDN algorithm not only shapes the error to frequencies to which the human visual system (HVS) is least sensitive but also shapes the error in colors to which the HVS is least sensitive— namely it satisfies the minimum brightness variation criterion. The correlation among the color planes by luminosity reduces the ormation of high contrast pixels, such as black and white pixels that often constitute color noise, resulting in a smoother and more homogeneous appearance in a halftone image and a closer resemblance to the continuous tone image.

Presented is a unique halftone geometric configuration for color halftone printing with an arbitrary number of colorants. The configuration uses a plurality of halftone screens to produce prints that are moiré free and possess uniform hexagonal periodic rosettes. Moiré-free N-color halftoning is achieved by selecting halftone frequencies from harmonics of two rosette fundamental frequencies. With such screen configurations, the interference between any halftone frequency components, fundamentals, or higher-order harmonics of different colorants is a linear integer combination of the two rosette fundamental frequencies. The linear integer combination produces a hexagonal grid of frequency components with no components lower than the rosette frequencies other than the zero-frequency component. Thus, no visible interference, or moiré, occurs within the halftone screen combinations. The observed halftone pattern is a visually pleasing, two-dimensionally uniformly repeated hexagonal rosette. The uniform-rosette configurations can be implemented using digital single-cell nonorthogonal halftone creens. The uniform-rosette method can be used with conventional cyan-magenta-yellow-black halftone printing or with printing systems that require a relatively large number of halftone screens. The additional screens can be used for enhanced printing applications, such as printing with high-fidelity colorants, light colorants, or special colorants, such as white, metallic, and fluorescent.

Halftoned separations of individual colorants, typically cyan, magenta, yellow, and black, are overlaid on a print substrate in typical color printing systems. Displacements between these separations, commonly referred to as “interseparation misregistration," can cause objectionable color shifts in the prints. We study this misregistration-induced color shift for periodic clustered-dot halftones using a spatiospectral model for the printed output that combines the Neugebauer model with a periodic lattice representation for the individual halftones. Using Fourier analysis in the framework of this model, we obtain an analytic characterization for the conditions for misregistration invariance in terms of colorant spectra, periodicity of the individual separation halftones, dot shapes, and misregistration displacements. We further exploit the framework in a hybrid analytical-numerical simulation that allows us to obtain quantitative estimates of the color shifts due to misregistration, thereby providing a characterization for these shifts as a function of the optical dot gain, halftone periodicities, spot shapes, and interseparation misregistration amounts. We present simulation results that demonstrate the impact of each of these parameters on the color shift and demonstrate qualitative agreement between our approximation and experimental data.

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×) in both the vertical and horizontal dimensions. The robustness of these algorithms to several common postprocessing algorithms is also evaluated.

This paper presents a robust copyright protection scheme based on discrete cosine transform (DCT) and secret sharing techniques. The scheme cannot only use a binary image of arbitrary size as the watermark, but also generate shares without the need of a codebook. The scheme first performs the DCT on a host image to obtain the image features and uses these features to generate a master share. The master share and a binary watermark are then used to generate an ownership share, according to the secret sharing technique. The hidden watermark, used for copyright verification, can be revealed by combining the master share with the ownership share. It is shown that the hidden watermark can be effectively revealed by the proposed scheme, even if the visual quality of protected images has been greatly degraded. Moreover, the proposed scheme achieves superior resistance to several image processing operations, compared with existing schemes.

By defining block image element, mixed image element (MIE), and composite image element (CIE), we propose a MIE encryption algorithm based on an elliptic curve cryptosystem (ECC), which extends the single image encryption algorithm to a multiple images encryption algorithm. The recipient’s (Bob’s) and the sender’s (Alice’s) detailed encryption and decryption steps and the core technology on the network platform are discussed. The correctness of this algorithm is verified. Experimental results and theoretical analysis show that the algorithm possesses large enough key space and can accomplish a high level of security concerning information interaction on the network platform. It can be particularly applicable to the highly confidential fields of information interaction. Finally, some problems in algorithm implementation are analyzed, and the prospects concerning the anomalous image element, rotary image element, and CIE encryption algorithms based on ECC are briefly described.

We propose a motion-compensation-based deinterlacing algorithm using global and representative local motion estimation. The proposed algorithm first divides an entire image into five regions of interest (ROIs) according to the temporally predicted motion type (i.e., global or local) and the spatial position. One of them is for global motion estimation and the others are for local motion estimation. Then, dominant motions of respective ROIs are found by adaptive projection approach. The adaptive projection method not only estimates dominant local motions with low computational cost, but also ensures consistent global motion estimation. Using the estimated motion vectors, adaptive two-field bidirectional motion compensation is performed. The arbitration rules, measuring the reliability of motion compensation accurately, produce high-quality deinterlaced frames by effectively combining the results of motion compensation and the stable intrafield deinterlacing. Experimental results show that the proposed deinterlacing algorithm provides better image quality than the existing algorithms in both subjective and objective measures.

We consider the transmission of progressive image data over noisy channels when the coded packet size is fixed. The concatenated cyclic redundancy check (CRC) codes and ratecompatible punctured turbo codes are used for error control and detection. In such an application, the distortion-based optimal channel rate allocation for unequal error protection is complex. We first propose a suboptimal genetic algorithm–based method that not only largely reduces the optimization complexity but also obtains performance approaching to the results of a brute force search. In addition, because a large packet size is usually applied when turbo codes are used due to the fact that the coding gain is proportional to the packet size for a given code rate, a single remaining bit error after channel decoding may result in CRC failure and hence the discard of the entire packet. Therefore, we further propose a multiple-CRC structure for certain data packets so that more correctly decoded data could be used in source decoding. The promising performance of the proposed scheme has been demonstrated through simulation.

Digital libraries became necessary vehicles that provide users with powerful and easy-to-use tools for searching, browsing, and retrieving media information. The starting point for these endeavors is the same: segmentation of video material into shots. The aim of this study is to segment MPEG video streams into shots. A fully automatic detection for both abrupt and gradual transitions (dissolve and fade groups) with minimal decoding in real time is developed. Each detection process was explored through two phases: macroblock type analysis in bidirectional predictive pictures (B-frames), and on-demand intensity information analysis. The abrupt transition detection is explored first by examining the number of forward and backward macroblocks (p- and b-MBs) in consecutive B-frames, and then an intensity histogram comparison is applied to confirm detected transitions. The gradual transition is detected first by examining the intracoded predicted macroblocks (i-MBs) within successive B-frames, and then the detection is confirmed by checking the parabolic shape of the frame variances of the candidate sequence. Results of the study show remarkable detection rate for both abrupt and gradual transitions.

We present a framework to classify the film categories based on low-level features and visual effect features. This approach can serve as a prefilter that represents the movies that you want to watch from the Internet or movie-on-demand service. Our current domain of study is the movie preview. In our approach, we categorize films into three broad kinds: action, drama, and thriller films. Four low-level video features (average shot length, color variance, lighting key, and motion content) and visual effects are combined in our system to provide helpful information to demonstrate the film category. The results indicate that visual effect features are effective and useful information and play an important role for classifying the film categories.

We present a collection of principles to compare two sets of color primaries for wide gamut displays. A new, algorithmic three-dimensional method to find optimal color primaries both for three-primary and multiprimary displays is described. The method was implemented in a computer program. The resulting optimal color primary sets are discussed. We show that two-dimensional methods to find optimal color primaries by using a chromaticity diagram are inferior to three-dimensional optimization techniques that include luminance information.

Several algorithms were proposed in the literature to recover the illuminant chromaticity of the original scene. These algorithms work well only when prior assumptions are satisfied, and the best and the worst algorithms may be different for different scenes. We investigate the idea of not relying on a single method but instead consider a consensus decision that takes into account the responses of several algorithms and adaptively chooses the algorithms to be combined. We investigate different combining strategies of state-of-the-art algorithms to improve the results in the illuminant chromaticity estimation. Single algorithms and combined ones are evaluated for both synthetic and real image databases using the angular error between the RGB triplets of the measured illuminant and the estimated one. Being interested in comparing the performance of the methods over large data sets, experimental results are also evaluated using the Wilcoxon signed rank test. Our experiments confirm that the best and the worst algorithms do not exist at all among the state-of-the-art ones and show that simple combining strategies improve the illuminant estimation.

We developed an experimental ultrahigh-definition color video camera [7680(H)×4320(V) pixels] using four 8-million-pixel charge-coupled devices (CCDs) to increase the camera’s resolution. This involves attaching four CCDs to a special color separation prism. Two CCDs are used for the green image; the other two are used for the red and blue images. Our prototype camera attains a limiting resolution of more than 2700 television lines, both horizontally and vertically. Camera sensitivity is F/2.8 at 2000 lux, with a luminance signal dark-noise level of approximately 50 dB in high definition television format. To analyze camera performance, we estimated the spatial position error between the two green CCDs and the chromatic aberration. Based on these estimations, the cause of resolution deterioration and ways to improve resolution are discussed.

Although many object invariant descriptors have been proposed in the literature, putting them into practice to obtain a robust recognition system that is able to face several perturbations is still a studied problem. After presenting the most commonly used global invariant descriptors, a comparative study permits us to show their ability to discriminate between objects with little training. The Columbia Object Image Library database (COIL-100), which presents a same object translated, rotated, and scaled, is used to test the invariant features of geometrical transforms. Partial object occultation or presence of complex background are examples of used images to test the robustness of the studied descriptors. We compare them in both a global and a local context (computed on the neighborhood of a pixel). The scale invariant feature transform descriptor is used as a reference for local invariant descriptors. This study shows the relative performance of invariant descriptors used in both a global and a local context and identifies the different situations for which they are best suited.

The turning angle function has been used as a signatureto represent the shape of a given contour with the aim of analysis ofshape and content-based image retrieval. We propose a methodthat uses the turning angle function to derive a polygonal model ofthe given contour in such a manner as to preserve the importantdetails in the contour. The preservation of diagnostically significantfeatures present in the contours of breast masses in mammogramsare important to discriminate between benign masses and malignanttumors. To evaluate the practical utility of the proposed polygonalmodeling method in terms of the efficiency in the classification ofbreast masses, we derive an index of spiculation SI_PMTF and a measureof fractional concavity F_cc from the models obtained and comparethe results with those provided by two methods proposed inprevious related works. The features SI_PMTF and F_cc were testedwith a set of 111 contours, of which 65 are related to benign massesand 46 are related to malignant tumors. High classification accuraciesof 0.93 with SI_PMTF and 0.91 with F_cc were obtained, in terms ofthe area under the receiver operating characteristics curve, with adata compression of 0.067 on the average.

Skin detection is a preliminary step in many applications. We analyze some of the most frequently cited binary skin classifiers based on explicit color cluster definition and present possible strategies to improve their performance. In particular, we demonstrate how this can be accomplished by using genetic algorithms to redefine the cluster boundaries. We also show that the fitness function can be tuned to favor either recall or precision in pixel classification. Some combining strategies are then proposed to further improve the performance of these binary classifiers in terms of recall or precision. Finally, we show that, whatever the method or the strategy employed, the performance can be enhanced by preprocessing the images with a white balance algorithm. All the experiments reported here have been run on a large and heterogeneous image database.

We propose image processing techniques for the detection of blood vessels in fundus images of the retina. The methods include the design of a bank of directionally sensitive Gabor filters with tunable scale and elongation parameters. Forty images of the retina from the Digital Retinal Images for Vessel Extraction database were used to evaluate the performance of the methods. The results of blood vessel detection using inverted green-channel images were compared with the corresponding manually segmented blood vessels. High efficiency in the detection of blood vessels with the area under the receiver operating characteristics curve of up to 0.96 was achieved with a combination of Gabor filters at three scales.

The problem of deformable objects in complex, cluttered environments is addressed. This approach, called the Cluster Tracker, concentrates on sectioning and tracking small features rather than the whole image as more conventional trackers do. Results indicate that the Cluster Tracker exhibits higher tracking reliability in heavily cluttered environments due to its ability to maintain track lock on objects even when they are partially obscured. The core of this method is based on an elastic matrix framework that supports a flexible structured model of the target. This approach allows the tracker to follow deformations of the target’s body shape and to estimate the location of occluded features.

A unique vision-based three-axis spacecraft attitude determination method using Moon or Earth observation images is introduced, which is able to operate in a stand-alone configuration. We describes the image data processing algorithms to extract the two directions needed from the observed images to estimate the spacecraft orientation. Since the image rotation and translation processes affect the attitude estimation result, the accuracy is quantified by analyzing the sensitivity of the two directions due to subpixel image translations and rotations. Furthermore, with the vision of a new Mars mission, an alternative image data processing algorithm for oblate bodies is presented. As for the attitude accuracy level that can be achieved, it highly depends on the image processing efficiency/complexity. Its numerical value, however, is not quantified because it would require unavailable real data.

This PDF file contains the errata for “JEI Vol. 17 Issue 02 Paper 2944173” for JEI Vol. 17 Issue 02

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