Edge Degradation Research Articles

Industrial computed tomography image size measurement

As one of the most useful modern detection technologies, Industrial Computed Tomography (ICT) image size measurement can correctly non-destructively measure the size of workpieces’ inner construction, and it is considered as the standard for quality assurance and reverse engineering. In view of the advantages and disadvantages compared to conventional methods, this paper improves the precision of image size measurement with a new algorithm that uses an approximate function to describe edge degradation. First, this algorithm constructs the approximate function and determines the optimal point of edge detection, based on image intensity and inflexions. Then, in order to accurately extract the image edge, this algorithm is used to revise the primary image, completing construction of the CT image. Excellent results are obtained from simulations and experiments. The experimental results indicate that the relative error is 2% for the CT image when the step evolution of the image edge is pooled. The relative error of this method is decreased by as much as 1.5% compared to wavelet transformation and ridgelet transformation. Therefore, this new algorithm demonstrates increased effectiveness in extracting an accurate measurement of the CT image edge.

Novel hybrid classified vector quantization using discrete cosine transform for image compression

We present a novel image compression technique using a classified vector Quantizer and singular value decomposition for the efficient representation of still images. The proposed method is called hybrid classified vector quantization. It involves a simple but efficient classifier-based gradient method in the spatial domain, which employs only one threshold to determine the class of the input image block, and uses three AC coefficients of discrete cosine transform coefficients to determine the orientation of the block without employing any threshold. The proposed technique is benchmarked with each of the standard vector quantizers generated using the k-means algorithm, standard classified vector quantizer schemes, and JPEG-2000. Simulation results indicate that the proposed approach alleviates edge degradation and can reconstruct good visual quality images with higher peak signal-to-noise ratio than the benchmarked techniques, or be competitive with them.

A G 2LA vector quantization for image data coding

In this paper, based on the Grey theory, a novel measurement method in a large volume and high dimension of information system is proposed for vector quantization (VQ) design and applied to image data coding. In the VQ coding procedure, it is often needs several epochs of clustering and always fails to obtain a better codebook; for instance, the well-known generalized Lloyd algorithm (GLA) easily traps into suboptimal codebook and does not have the ability to locate an optimal codebook during any clustering iteration with a random initial codebook. Hence, we propose a G 2LA design to solve heavy times of clustering procedure and at least to gain the best suboptimal codebook. In order to avoid edge degradation, firstly, the new selection of initial codevectors is adopted as the fast grey vector quantization (FGVQ) procedure which chooses nonhomogeneous vectors from a large volume image data. Then extending the GLA to G 2LA method by utilizing the measurement of grey relational analysis (GRA) which depends on the effect of relative objective and initial codevectors of FGVQ to obtain a better representative codebook. Experiment results show that at the same bit rate the G 2LA has not only the quickly convergence time but also high quality reconstructed image than traditional GLA technique with Euclidean distance measure, especially in high dimension and a large volume data system.

SU‐GG‐T‐319: Monte Carlo Study of Distal Edge Degradation in Proton Therapy Due to Heterogeneities. Proof of Principle with a Case Study

Purpose: Degradation of the distal edge of quasi‐mono energetic proton beams occurs when the proton beams penetrate geometries containing complex inhomogeneities. Contemporary treatment planning systems fail to accurately predict the degradation and its potential consequences, such as dose spill over into healthy tissue or the effects on dose homogeneity in the target volume. This work aimed to build a Monte Carlo model which accurately predicts the degradation. Method and Materials: In this study we built an MCNPX Monte Carlo model to simulate this degradation in a scanning‐beam nozzle, using a 221.83 MeV proton beam impinging on a voxelized computer tomography‐based phantom of a human head. Dose distributions, energy and angular distributions of the proton beam were tallied in and at the surface of a water phantom distal to the CT‐based human head phantom. Results: It was found that the degradation of the distal edge and the energy distribution of the proton beams are strongly correlated to the complexity of the heterogeneity. The angular spread of the beam showed only a weak dependence. Conclusion: The Monte Carlo simulation model successfully produced the degradation of proton beams through a heterogeneous environment. It will be a useful tool to investigate the basic underlying physics and provide support for the development of optimization tools for proton therapy treatment planning and help to achieve escalated target doses and minimize collateral damage to normal tissue.

Image compression using improved hybrid classified vector quantisation

A novel image compression technique using classified vector quantiser and singular value decomposition is proposed for the efficient representation of still images. The proposed method is called improved hybrid classified vector quantisation. The proposed technique was benchmarked with the standard vector quantiser generated using the k-means algorithm, and JPEG-2000. Simulation results indicate that the proposed approach alleviates edge degradation and can reconstruct good visual quality images with higher peak signal-to-noise ratio than the benchmarked techniques.

3D characterisation of tool wear whilst diamond turning silicon

Nanometrically smooth infrared silicon optics can be manufactured by the diamond turning process. Due to its relatively low density, silicon is an ideal optical material for weight sensitive infrared (IR) applications. However, rapid diamond tool edge degradation and the effect on the achieved surface have prevented significant exploitation. With the aim of developing a process model to optimise the diamond turning of silicon optics, a series of experimental trials were devised using two ultra-precision diamond turning machines. Single crystal silicon specimens (1 1 1) were repeatedly machined using diamond tools of the same specification until the onset of surface brittle fracture. Two cutting fluids were tested. The cutting forces were monitored and the wear morphology of the tool edge was studied by scanning electron microscopy (SEM). The most significant result showed the performance of one particular tool was consistently superior when compared with other diamond tools of the same specification. This remarkable tool performance resulted in doubling the cutting distance exhibited by the other diamond tools. Another significant result was associated with coolant type. In all cases, tool life was prolonged by as much as 300% by using a specific fluid type. Further testing led to the development of a novel method for assessing the progression of diamond tool wear. In this technique, the diamond tools gradual recession profile is measured by performing a series of plunging cuts. Tool shape changes used in conjunction with flank wear SEM measurements enable the calculation of the volumetric tool wear rate.

CUDI: A model for calculation of electrodynamic and thermal behaviour of superconducting Rutherford cables

CUDI is the extended Fortran code to calculate the electrodynamic and thermal behaviour of any type of Rutherford cable subject to global and/or local variations in field, transport current, and external heat release. The internal parameters of the cable can be freely varied along the length and across the width, such as contact resistances, critical current, cooling rates etc. In this way, all the typical non-uniformities occurring in a cable, e.g. broken filaments, strand welds, cable joints, and edge degradation can be simulated. Also the characteristics of the strands in the cable can be varied from strand to strand. Heat flows through the matrix, through the interstrand contacts, and to the helium are incorporated, as well as the self-field and self- and mutual inductances between the strands. The main features and structure of the program will be discussed.

New Model of Charge Generation and Latent Image Degradation in Single Layer Organic Photoconductor

A new model of charge generation process in the single layer organic photoconductor (OPC) was proposed where the charge generation took place at the surface of the photoconductive layer after phonon diffusion from within the photoexcited bulk photoconductive layer. The degradation of the edge sharpness of the electrostatic latent image was simulated theoretically according to this model and the parameters that dominated the resolution degradation in the single layer OPC due to the energy diffusion were determined. The analytical result suggested the model of edge degradation in this system depended strongly on the phonon diffusion length. Accordingly, an experimental analysis was performed that explained the dependence of diffusion length on the photoreceptor formulation. The experimental result showed the validity of the principle in the proposed model for all OPC formulations tested, and the existence of a significant dependence of diffusion length on the CGM concentration in the photosensitive layer. The obtained results numerically showed the superiority in resolution of the single layer OPC compared with those of the conventional dual layer OPC, suggesting the possibility of true 2400 DPI imaging. The results provided a guideline for realizing higher resolution imaging via the single layer OPC formulation.

A new cluster validity measure and its application to image compression

Many validity measures have been proposed for evaluating clustering results. Most of these popular validity measures do not work well for clusters with different densities and/or sizes. They usually have a tendency of ignoring clusters with low densities. In this paper, we propose a new validity measure that can deal with this situation. In addition, we also propose a modified K-means algorithm that can assign more cluster centres to areas with low densities of data than the conventional K-means algorithm does. First, several artificial data sets are used to test the performance of the proposed measure. Then the proposed measure and the modified K-means algorithm are applied to reduce the edge degradation in vector quantisation of image compression.

A measure for assessing edge fidelity of coded images based on shape analysis

AbstractThe authors propose a method for quantifying the edge degradation of a coded image produced by aliasing distortion or block distortion based on the change in its shape. Essentially, when a change is generated in a smooth portion, a human can quickly detect it. With conventional techniques based on signal differences, it was difficult to assess a geometric distortion for which continuity or uniformity changed. The proposed technique obtains mutually corresponding edge segments for the original image and coded image and quantifies the shape degradation based on their curvature. To match subjective assessments, the measure that was obtained takes into consideration (1) the spatial size of the shape change, (2) the shape error masking effect, and (3) the edge gradient (contrast) effect in the quantification process. The authors performed simulations for several standard images while changing the coding rate and coding method, and the results that were obtained reflected the impressions of the images well. © 2004 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 87(8): 9–23, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjc.10157

On the skew-bounded minimum-buffer routing tree problem

Bounding the load capacitance at gate outputs is a standard element in today's electrical correctness methodologies for high-speed digital very large scale integration design. Bounds on load caps improve coupling-noise immunity, reduce degradation of signal transition edges, and reduce delay uncertainty due to coupling noise (Kahng et al. 1998). For clock and test distribution, an additional design requirement is bounding the buffer skew, i.e., the difference between the maximum and the minimum number of buffers over all of the source-to-sink paths in the routing tree, since buffer skew is one of the main factors affecting delay skew (Tellez and Sarrafzadeh 1997). In this paper, we consider algorithms for buffering a given tree with the minimum number of buffers under given load cap and buffer skew constraints. We show that the greedy algorithm proposed by Tellez and Sarrafzadeh is suboptimal for nonzero buffer-skew bounds and give examples showing that no bottom-up greedy algorithm can achieve optimality. The main contribution of the paper is an optimal dynamic programming algorithm for the problem. Experiments on test cases extracted from recent industrial designs show that the dynamic programming algorithm has practical running time and saves up to 37.5% of the buffers inserted by Tellez and Sarrafzadeh's algorithm.

Minimum buffered routing with bounded capacitive load for slew rate and reliability control

In high-speed digital VLSI design, bounding the load capacitance at gate outputs is a well-known methodology to improve coupling noise immunity, reduce degradation of signal transition edges, and reduce delay uncertainty due to coupling noise. Bounding load capacitance also improves reliability with respect to hot-carrier oxide breakdown and AC self-heating in interconnects, and guarantees bounded input rise/fall times at buffers and sinks. This paper introduces a new minimum-buffer routing problem (MBRP) formulation which requires that the capacitive load of each buffer, and of the source driver, be upper-bounded by a given constant. Our contributions are as follows: We give linear-time algorithms for optimal buffering of a given routing tree with a single (inverting or noninverting) buffer type. For simultaneous routing and buffering with a single noninverting buffer type, we prove that no algorithm can guarantee a factor smaller than 2 unless P=NP and give an algorithm with approximation factor slightly larger than 2 for typical buffers. For the case of a single inverting buffer type, we give an algorithm with approximation factor slightly larger than 4. We give local-improvement and clustering based MBRP heuristics with improved practical performance, and present a comprehensive experimental study comparing the runtime/quality tradeoffs of the proposed MBRP heuristics on test cases extracted from recent industrial designs.

Measurement and origin of tape edge damage in a linear tape drive

Integrity of the magnetic tape edge is the key to maintaining high performance of modern tape drives. Damage to the tape edge under normal drive operation results in the change in tape dimensions and debris generation, both leading to degradation in the reproduction of the recorded signal. The objective of the present study is to develop a methodology for evaluation of tape edge quality and to apply the methodology to monitor tape edge degradation under normal drive operation. Optical microscopy, atomic force microscopy and scanning electron microscopy are employed to study and quantify the quality of the tape edge. AFM measure-ments were made on both individual tape layers and the tape reel. An edge quality measurement technique is used to quantify the damage to tape edge. A technique for the tape lateral motion measurement is used to study the effect of continuous sliding on tape guiding. A lateral force measurement technique is developed to measure the force exerted by the tape edge on the guide flange. The effect of normal drive operation on tape edge quality and on tape guiding in a linear tape drive is studied. It is shown that two edges of a factory-slit tape are imperfect and different, with cracking of the magnetic coating occurring at one edge. Under normal drive operation, one edge experiences more wear with larger amount of debris produced. This larger debris generation occurs on the edge with cracks developed during manufacturing. A possible mechanism of tape edge wear under normal drive operation is proposed.

Three-dimensional Region-based Filters for Noise Removal in Volumetric Data

We present region-based filters for noise removal in three-dimensional (3D) images in the (x, y, z) domain. The filters start with region growing at each voxel to determine a context-dependent region in 3D. Appropriate selection of region-growing criteria provides regions that approximate 3D objects or features present in the image. Local statistics are then used to filter noise. The method permits adaptive noise removal without degradation of edges, surfaces, or shapes of objects. Results of 3D region-based mean, median, and local linear minimum mean-squared error (LLMMSE) filtering are shown, along with results of two-dimensional (2D) region-based filtering on a slice-by-slice basis, as well as 2D and 3D fixed-neighborhood filtering. Results of 3D region-based filtering possess lower mean-squared errors (MSE) than the results of fixed-neighborhood filters in 3D or 2D. Furthermore, results of 3D region-based filtering possess MSE lower than or equal to the MSE of the results of 2D region-based filtering because 3D filtering exploits the presence of 3D structures in the images. The methods should be applicable in processing of 3D medical images and as a pre-processing step in volume visualization.

Geobotanical indication of the state of suburban forests (an example of birch grove in Akademgorodok, Krasnoyarsk).

The influence of recreation activity on grass cover was studied in a herbaceous birch forest within a territory of city development. Effects of the activity depended on size and arrangement of recreation sites. It was found that most of the forest was at the second stage of degradation, while degradation of forest edges was considered as intermediate between the second and third stages. Forest edges and glade-clump communities play a particular role in maintaining the stability of recreational forests.These ecotones are both barriers preventing introduction of alien plant species into a cenosis and centers of dissemination of ruderal and meadow species.

Postprocessing of low bit-rate wavelet-based image coding using multiscale edge characterization

In this paper, we propose a new postprocessing method for low bit-rate wavelet-based image coding which uses the technique of wavelet modulus maximum representation (WMMR). The edge degradation from wavelet-based coding is discussed under the overcomplete wavelet expansion, and interpreted as the distortion of wavelet modulus maxima, i.e., magnitude decays. Based on the empirical analysis and experimental results, we develop a set of compensation functions to restore the distorted wavelet modulus maxima of a coded image. Therefore, we can enhance the image quality for low bit-rate wavelet coding by reconstructing the coded image using the WMMR with improved visual quality and image fidelity (peak signal-to-noise ratio).

A technique using peano scanning for vector quantization with variable codevector dimensions

In this paper, a new direction for Vector Quantization is proposed. To reduce the blocky effect and edge degradation, we combine Peano Scan and VQ ( PSVQ) to achieve this goal in our implementation. All training images (512×512) are reordered to 1D space by efficient Peano Scan in advance. We classify 4 different partition segments including 1×8, 1×16, 1×32, and 1×64 dimensions according to the difference between the maximum and the minimum intensities in the 1D segment. Simulation results show that the performance of the suggested scheme is superior to the normal VQ scheme in the sense of PSNR, and both the edge degradation and the blocky effect is reduced.

Model-based edge reconstruction for low bit-rate wavelet-compressed images

At low bit rates, wavelet-based image coding is superior to most traditional block-based methods in terms of visibility and severity of coding artifacts in coded images. However, the compressed images still suffer from obvious distortions around sharp edges, which are perceptually objectionable. In order to improve the image quality for low bit-rate wavelet-based image coding, we proposed a model-based edge-reconstruction algorithm for recovering the lossy edges in coded images. Our approach applies a general model to represent varieties of edges existing in an image. Based on this model, the edge degradation process due to quantization errors of wavelet coefficients is analyzed with the characterization of two kinds of artifacts at edges. We develop two operations, model-based edge approximation and Gaussian smoothing, to reconstruct distorted edges by reducing both artifacts respectively. The proposed method is able to improve the image quality in terms of both visual perception and image fidelity (peak signal-to-noise ratio) for most images coded by wavelet-based methods at low bit-rates.

Pixel-Pixel Electrical “Cross Talk” Through Liquid Toner Developer and Resultant Image Degradation

One normally conceptualizes and analyzes electrophotographic liquid toner development as proceeding strictly between an electrically-biased developer electrode and a photoreceptor, with a more or less “perpendicularly-constrained” development current flow. That is, one typically ignores the “local lateral conduction” through the liquid toner near the photoreceptor surface which tends to “short-together” the closelyspaced, adjacent image pixels which are at different surface potentials. In this paper, an analog electronic circuit model is used to analyze dynamically the local lateral electric currents through the liquid toner close to the photoreceptor surface, driven by adjacent image pixels at different initial potentials. This is herein termed “pixel-pixel cross talk.” It presents a quantitative and comprehensive, dynamic “picture” of the lateral current transients (cross talk currents) as the image pixels traverse the development nip, along with the resultant edge degradation and “single-pixel-fill-in.” It predicts and demonstrates the effects of development gap, liquid toner conductivity, photoreceptor thickness, process speed, etc., and whether changes in these parameters will ameliorate or aggravate the image degradation. The circuit model results are in excellent agreement with experiment; give powerful additional insight into the transient dynamics of the cross talk effects, and suggests ways to reduce the degradation.

Fractal coding of subbands with an oriented partition

Abstract We propose a new image compression scheme based on fractal coding of the coefficients of a wavelet transform, in order to take into account the self-similarity observed in each subband. The original image is first decomposed into subbands containing information in different spatial directions and at different scales, using an orthogonal wavelet-generated filter bank. Subbands are encoded using local iterated function systems (LIFS), with range and domain blocks presenting horizontal or vertical directionalities. Their sizes are defined according to the correlation lengths and resolution of each subband. The edge degradation and the blocking effects encountered at low bit-rates using conventional LIFS algorithm are reduced with this approach. The computation complexity is also greatly decreased by a 12:1 factor in comparison to fractal coding of the full resolution image. The proposed method is applied to standard test images. The comparison with other fractal coding approaches and with JPEG shows an important increase in terms of PPSNR/bit-rate. Especially for images presenting a privileged directionality, the use of adaptive partitions results in about 3 dB improvement in PPSNR. We also discuss the distorsion versus rate improvement obtained on high-frequency subbands when fractal coding instead of pyramidal vector quantization is used. Our approach achieves a real gain in PPSNR for low bit-rates between 0.3 and 1.2 bpp.