Edge Detection Procedure Research Articles

Ultrasonic C-scan detection for stainless steel spot welding based on wavelet package analysis

An ultrasonic test of spot welding for stainless steel is conducted. Based on wavelet packet decomposition, the ultrasonic echo signal has been analyzed deeply in time - frequency domain, which can easily distinguish the nugget from the corona bond. The 2D C-scan images produced by ultrasonic C scan which contribute to quantitatively calculate the nugget diameter for the computer are further analyzed. The spot welding nugget diameter can be automatically obtained by image enhancement, edge detection and equivalent diameter algorithm procedure. The ultrasonic detection values in this paper show good agreement with the metallographic measured values. The mean value of normal distribution curve is 0.006 67, and the standard deviation is 0.087 11. Ultrasonic C-scan test based on wavelet packet signal analysis is of high accuracy and stability.

Image-Processing-Based Transceiver Design for Acoustic PPM Underwater Links

Underwater pulse position modulation (PPM) transmission uses acoustic pulses since they allow communication, remote control of underwater vehicles, and positioning estimation; the last one when more than one detector is present by using only one technology, that is, the same transmission module. On the other hand, PPM pulses are difficult to detect since they carry information on signal delays, assuring that reliable information delivery both in shallow- and deep-sea channels may be considered a timely challenge due to strong multipath and other interference sources/causes giving rise to signal fluctuation and high noise level. This paper proposes a transceiver architecture characterized by a signal analyzer and an adaptive detection based on the channel features. The signal analysis is based on the Wigner–Ville transform (WVT) that converts a 1-D signal into an image. Edge detection procedures performed on the obtained image so as to discover the interference features and understand the main characteristics of multipath with their adverse effects on detection of pulse position information have been taken into account. Based on this, maximal ratio combining (MRC) and equal gain combining (EGC) for RAKE reception and truncated channel equalization have been considered. Numerical results showing the ability of the proposed transceiver to detect pulses in the presence of multipath and interference generated by external acoustic sources have been carried out also by taking into account the estimation error effects and by comparing the actual performance with ideal cases. Finally, field tests corroborate the reliability of the proposed approach.

A novel image edge detection algorithm based on neutrosophic set

Neutrosophic set (NS) theory is a formal framework to study the origin, nature, and scope of the neutral state. In this paper, neutrosophic set is applied in image domain and a new directional α-mean operation is defined. Based on this operation, neutrosophic set is applied into image edge detection procedure. First, the image is transformed into NS domain, which is described by three membership sets: T, I and F. Then, a directional α-mean operation is employed to reduce the indeterminacy of the image. Finally, a neutrosophic edge detection algorithm (NSED) is proposed based on the neutrosophic set and its operation to detect edge. Experiments have been conducted using numerous artificial and real images. The results demonstrate the NSED can detect the edges effectively and accurately. Particularly, it can remove the noise effect and detect the edges on both the noise-free images and the images with different levels of noises.

SİMAV HAVZASININ JEOFİZİK VERİLERLE ANALİZİ VE MODELLENMESİ, BATI ANADOLU

The various data processing techniques, to illuminate the parameters of the geologicalstructure which are applied in gravity and magnetic potential field methods. Also edgedetection procedures are in data processing techniques. In this study, 2D, 3D, inversionand asta technique is one of the new edge detection procedures were applied to clarifycorrelation between the Simav half graben’s deep position and geometry of the tectoniclineaments. The Asta is obtained using the tilt angle

Study of edge detection task in dental panoramic radiographs

The purpose of this study is (1) to introduce a new approach for edge detection in orthopantograms (OPGs) and an improved automatic parameter selector for common edge detectors, (2) to present a comparison between our novel approach with common edge detectors and (3) to provide faster outputs without compromising quality. A new approach for edge detection based on statistical measures was introduced: (1) a set of N edge detection results is calculated from a given input image and a selected type of edge detector, (2) N correspondence maps are constructed from N edge detection results, (3) probabilities and average probabilities are computed, (4) an overall correspondence is evaluated for each correspondence map and (5) the correspondence map providing the best overall correspondence is taken as the result of edge detection procedure. A comparison with common edge detectors (the Roberts, Prewitt, Sobel, Laplacian of the Gaussian and Canny methods) with various parameter settings (304 combinations for each test image) was carried out. The methods were assessed objectively [edge mismatch error (EME), modified Hausdorff distance (MHD) and principal component analysis] and subjectively by experts in dentistry and based on time demands. The suitability of the new approach for edge detection in OPGs was confirmed by experts. The current conventional methods in edge detection in OPGs are inadequate (none of the tested methods reach an EME value or MHD value below 0.1). Our proposed approach for edge detection shows promising potential for its implementation in clinical dentistry. It enhances the accuracy of OPG interpretation and advances diagnosis and treatment planning.

NOISE REDUCTION METHOD FOR OCT IMAGES BASED ON EMPIRICAL MODE DECOMPOSITION

In this paper, the new method for OCT images denoizing based on empirical mode decomposition (EMD) is proposed. The noise reduction is a very important process for following operations to analyze and recognition of tissue structure. Our method does not require any additional operations and hardware modifications. The basics of proposed method is described. Quality improvement of noise suppression on example of edge-detection procedure using the classical Canny's algorithm without any additional pre- and post-processing operations is demonstrated. Improvement of raw-segmentation in the automatic diagnostic process between a tissue and a mesh implant is shown.

Assessment of accuracy and repeatability of anterior segment optical coherence tomography and reproducibility of measurements using a customised software program

Purpose: The aim was to study the reliability of measurements of the RTVue (Optovue, Fremont, CA, USA) anterior segment optical coherence tomographer (AS‐OCT) and assess how results can be improved by analysing raw optical coherence tomography data with customised image analysis software and applying correction factors.Methods: Five RTVue AS‐OCT instruments (ver. 4.0) were assessed by imaging gauge blocks of three different lengths, single/stepped glass plate (microscope slides) and flat window glass to check for width, depth and linearity of the measurement scans. Five repeats per calibration tool were imaged and averaged. Raw data were exported and loaded into customised image analysis software written in LabWindows/CVI for further analysis. Using two calibration balls with different radii, measurement scans were validated. Repeatability of the optical coherence tomographs and the edge detection procedure were checked and statistical analyses performed.Results: Variations ranging from 0.01 to 1.93-mm in scan width and 0.1 to 0.17-mm in scan depth were found between the five instruments. Slight curvature distortion of 0.06 ± 0.01-mm (mean and standard deviation) was found in the raw images. By isolating the three sources of image distortion and applying individual correction factors, accuracy for corneal curvature measurements could be improved to better than 0.1-mm. Manual edge detection limited the coefficient of repeatability value to 0.06 and 0.08-mm for anterior and posterior radii of curvature, respectively. The coefficient of repeatability of corneal thickness measurements was less than 8 µm.Conclusions: Accuracy of the RTVue AS‐OCT varied between instruments. By applying calibration scale factors calculated by customised software, accuracy of thickness and curvature values of the anterior eye was improved. The achievable precision is sufficient to detect clinically relevant corneal curvature variations.

A Combined Method for Concentric Circles Detection in Image of O-Shape Rubber Ring

Traditional Hough transform (HT) methods based on parameters decomposition do not give good result for concentric circle detection, for the reasons of its large amount of calculations, high demand of storage space and low efficiency in real-time application. To compensate the weaknesses, this paper employs a kind of improved Hough transform method which aims at reducing the parameters space. In this paper, the detection method is further improved through adding an edge detection procedure based on global threshold. The experimental results show that this algorithm meets the on-line detection of high accuracy requirement, with superior real-time performance and stronger anti-interference ability.

Measurement of micron level distortions in a macroscopic cylindrical object from x-ray CT images

A technique for the measurement or tracking of fine distortion in macroscopic objects of nominally circular section is described and assessed. Distortions of order several microns have been measured in a 14cm diameter, thick-walled polymethyl methacrylate (PMMA or Perspex) cylinder by tracking the location of multiple edge points of the object in its x-ray CT images using the circle-PLUS subpixel edge detection procedure. The cylinder was deformed by compressing it along a diameter over a total range of 340μm (0.7pixel in its CT image) in 10 steps. The successive cylinder wall deflections in the direction of the compression, and the corresponding deflections in the perpendicular direction, were calculated from images obtained using a GE Lightspeed medical CT scanner. The calculated shifts in cylinder diameter were compared directly with mechanical measurements obtained with a micrometer. The minimum detectable shift in object diameter of 0.033pixel or 1/30th of a pixel (16μm) was calculated from the image and verified by mechanical measurement. The circle-PLUS edge detection procedure should be applicable to both precision industrial measurements and clinical measurements such as vessel or bone dimensions or applications requiring precise organ size, shape or position determination. The procedure is not restricted to x-ray CT applications and could also be readily applied to precision optical measurements or MRI data.

Historical changes in seagrass coverage on the Mississippi barrier islands, northern Gulf of Mexico, determined from vertical aerial imagery (1940–2007)

Vertical aerial image data were used with an edge-detection procedure and visual image interpretation to determine yearly to decadal changes in seagrass (predominantly Halodule wrightii Ascherson) coverage on the Mississippi barrier islands. On Horn Island, seagrass coverage declined from 77 ha in 1940 to 19 ha in 1971, but returned to its 1940 value by 2006. Coverage on Petit Bois declined from 54 ha in 1940 to 8–19 ha from 1952 through 2007. On East Ship, seagrass coverage varied at 2–19 ha from 1963 to 2007. On West Ship, coverage dropped to zero in 2003, but by 2007 it had increased to approximate its 1975 value of 1.8 ha. On Cat Island, coverage increased from 22 ha in 2003 to 71 ha in 2007. There was no apparent negative impact of Hurricane Camille or Hurricane Katrina on seagrass coverage, which could vary annually by a factor of two or more.

The Canny Edge Detector Revisited

Canny (IEEE Trans. Pattern Anal. Image Proc. 8(6):679-698, 1986) suggested that an optimal edge detector should maximize both signal-to-noise ratio and localization, and he derived mathematical expressions for these criteria. Based on these criteria, he claimed that the optimal step edge detector was similar to a derivative of a gaussian. However, Canny's work suffers from two problems. First, his derivation of localization criterion is incorrect. Here we provide a more accurate localization criterion and derive the optimal detector from it. Second, and more seriously, the Canny criteria yield an infinitely wide optimal edge detector. The width of the optimal detector can however be limited by considering the effect of the neighbouring edges in the image. If we do so, we find that the optimal step edge detector, according to the Canny criteria, is the derivative of an ISEF filter, proposed by Shen and Castan (Graph. Models Image Proc. 54:112---133, 1992). In addition, if we also consider detecting blurred (or non-sharp) gaussian edges of different widths, we find that the optimal blurred-edge detector is the above optimal step edge detector convolved with a gaussian. This implies that edge detection must be performed at multiple scales to cover all the blur widths in the image. We derive a simple scale selection procedure for edge detection, and demonstrate it in one and two dimensions.

Edge detection within qualitative phase contrast neutron radiographies of castings

Qualitative phase contrast (QPC) imaging is a powerful tool to assess objects or composites with low or nearly the same attenuation coefficient resulting in a low absorption contrast. QPC imaging provides additional information like enhanced contrast at edges and interfaces as well as the possibility to separate materials with similar attenuation coefficients. The measurements are carried out at the neutron radiography facility ANTARES (Advanced Neutron Tomography and Radiography Experimental System), which fulfills the requirements for QPC imaging: a high transversal spatial coherence and a detector plane in the near-field region. We take QPC tomographies of a specially designed aluminum casting. In this work, the focus is on the image processing of QPC neutron radiographies, especially on edge and line detection and separation. For our purpose, we have evaluated different state of the art 2-D edge detection algorithms. Among our tested image post-processing algorithms, the best suitable procedure for edge and line detection on large and small scales have been identified.

A run‐based procedure to identify time‐lagged gene clusters in microarray experiments

The analysis of gene-expression data obtained from microarray experiments can be useful to identify regulatory relationship between genes. Genes with a common functional role have similar expression patterns across different microarray experiments. These similar expression patterns are perhaps due to co-regulation of genes in the same functional group. Most of the existing methods available for the identification of the regulatory relationships are either made for comparing two genes at a time or methods are not computationally efficient in the identification of the regulatory relationships. The procedures adopted by these methods do not use complete information contained in the data set. In this paper, we propose a statistical procedure, which will use the information contained in the data set to cluster genes that show similar patterns. The proposed procedure compares several genes at a time instead of pair-wise comparisons as done in some of the other procedures. The proposed procedure provides gene clusters based on time-lagged data sets with more details. The proposed method provides a numerical value that would facilitate in comparing different sets of data obtained from different expressions. It also provides the identification of the gene involved and the time point at which the observation is made so that proper medicine can be developed for the gene-specific and time-specific disease. We applied the proposed procedure on the Spellman data set (Mol. Biol. Cell 1998; 9(12): 3273-3297) and compared our procedure with some of the other existing procedures. We found that our procedure is more computationally efficient than Ji and Tan (Bioinformatics 2005; 21:509-516), event method and edge detection procedures. The proposed procedure also provides more details about the clusters than Ji and Tan (Bioinformatics 2005; 21:509-516), event method and edge detection procedures. The proposed procedure is really simple to apply as compared with other available procedures in the literature including Ji and Tan (Bioinformatics 2005; 21:509-516), event method and edge detection procedures.

Rise dynamics and relative ash distribution in vulcanian eruption plumes at Santiaguito Volcano, Guatemala, revealed using an ultraviolet imaging camera

Santiaguito Volcano, Guatemala, regularly produces small vulcanian eruption plumes which rise to heights of up to 2 km. A combined study using a novel UV camera coupled with classical analysis of the fluid dynamics of finite‐volume buoyant releases (thermals) has been used to develop a detection algorithm for ground‐based volcanic ash monitoring. Analysis of plume rise dynamics shows that vulcanian eruption plumes at Santiaguito behave as axisymmetric buoyant thermals, and this behaviour is consistent with eruption of volcanic gas and particle mixtures whose initial momentum is dissipated by flow through a porous capping layer. The UV imager has been adapted to detect relative ash burdens through the use of a single filter, centred on 307 nm, an edge detection and background fitting procedure and normalising to a simple theoretical model. The method provides the capability to observe and measure the internal structure of the plume, and processes occurring during plume rise, including concentration of ash over time into the thermal ‘head’, increased ash at the plume edges during early formation of the thermal and dilution at the top of the plume head as entrainment occurs.

Edge Histogram Descriptor in Wavelet Domain Based on JPEG2000

Due to the decoding procedure and filtering for edge detection, the feature extraction process of MPEG-7 Edge Histogram Descriptor (EHD) is time-consuming and computationally expensive. We proposed the fast EHD generation method in wavelet domain of JPEG2000 images. Experimental results demonstrate the advantage of this method over EHD.

A computer system to rate the color-related formal elements in art therapy assessments

The authors consider the colors used in a drawing to be one of the most important factors in art therapy assessments. This paper delineates the development of a computer system designed to rate several color-related elements, including the number and list of the colors used, elements common in art therapy assessments. We propose other possible elements such as the number of clusters for each color, the area of each color, and the length of edges where one color changes to another. These elements can provide useful information on patients, but their accuracy and objective ratings have been hard to obtain by human raters. We devise computer methods of color recognition and edge detection. The proposed color recognition procedure adopts the National Bureau Standard's criterion for distance between colors in the HVC (Hue, Value, Chroma) color space. The edge detection procedure applies blurring, clustering, and transformation to a standard color. The system can provide more accurate, detailed, objective, and new rating scales related to color. It can also reduce the time and effort of human raters. The proposed system is verified through case studies, application to an existing rating system, and analysis of sample results.

A hybrid multi-scale model for thyroid nodule boundary detection on ultrasound images

A hybrid model for thyroid nodule boundary detection on ultrasound images is introduced. The segmentation model combines the advantages of the “á trous” wavelet transform to detect sharp gray-level variations and the efficiency of the Hough transform to discriminate the region of interest within an environment with excessive structural noise. The proposed method comprise three major steps: a wavelet edge detection procedure for speckle reduction and edge map estimation, based on local maxima representation. Subsequently, a multiscale structure model is utilised in order to acquire a contour representation by means of local maxima chaining with similar attributes to form significant structures. Finally, the Hough transform is employed with ‘a priori’ knowledge related to the nodule's shape in order to distinguish the nodule's contour from adjacent structures. The comparative study between our automatic method and manual delineations demonstrated that the boundaries extracted by the hybrid model are closely correlated with that of the physicians. The proposed hybrid method can be of value to thyroid nodules’ shape-based classification and as an educational tool for inexperienced radiologists.

WHEEZE RECOGNITION BASED ON 2D BILATERAL FILTERING OF SPECTROGRAM

This paper describes the design of a low-cost and high performance wheeze recognition system. First, respiratory sounds are captured, amplified and filtered by an analog circuit; then digitized through a PC soundcard, and recorded in accordance with the Computerized Respiratory Sound Analysis (CORSA) standards. Since the proposed wheeze detection algorithm is based on the spectrogram processing of respiratory sounds, spectrograms generated from recorded sounds have to pass through a 2D bilateral filter for edge-preserving smoothing. Finally, the processed spectra go through an edge detection procedure to recognize wheeze sounds.Experiment results show a high sensitivity of 0.967 and a specificity of 0.909 in qualitative analysis of wheeze recognition. Due to its high efficiency, great performance and easy-to-implement features, this wheeze recognition system could be of interest in the clinical monitoring of asthma patients and the study of physiological mechanisms in the respiratory airways.

Adaptive Edge Detectors for Piecewise Smooth Data Based on the minmod Limiter

We are concerned with the detection of edges--the location and amplitudes of jump discontinuities of piecewise smooth data realized in terms of its discrete grid values. We discuss the interplay between two approaches. One approach, realized in the physical space, is based on local differences and is typically limited to low-order of accuracy. An alternative approach developed in our previous work [Gelb and Tadmor, Appl. Comp. Harmonic Anal., 7, 101---135 (1999)] and realized in the dual Fourier space, is based on concentration factors; with a proper choice of concentration factors one can achieve higher-orders--in fact in [Gelb and Tadmor, SIAM J. Numer. Anal., 38, 1389---1408 (2001)] we constructed exponentially accurate edge detectors. Since the stencil of these highly-accurate detectors is global, an outside threshold parameter is required to avoid oscillations in the immediate neighborhood of discontinuities. In this paper we introduce an adaptive edge detection procedure based on a cross-breading between the local and global detectors. This is achieved by using the minmod limiter to suppress spurious oscillations near discontinuities while retaining high-order accuracy away from the jumps. The resulting method provides a family of robust, parameter-free edge-detectors for piecewise smooth data. We conclude with a series of one- and two-dimensional simulations.

그림진단을 위한 주제색 및 불균형 판단의 자동화

Art psychotherapy is widely accepted as an effective tool for diagnosis and treatment of psychological disorders. Important factors for art psychotherapy diagnosis, based on the projection theory that the world of the inner mind appears in drawings, include main color and imbalance of a drawing. This paper develops a system for a machine to determine the main color and the imbalance of a drawing by color recognition and edge detection. Our proposed color recognition procedure adopts NBS(National Bureau of Standards) distance between colors in HVC(Hue, Value, Chroma) color space which is most similar to the human eye`s color perception. Our edge detection procedure applies blurring, clustering and transformation to a standard color in a series. Our system considers the numbers of pixels and clusters for each color as a criterion for main color and the frequency of edge coordinates for each region for imbalance. The proposed machine procedure, verified through case studies, can help overcome the subjectivity, ambiguity and uncertainty in human decision involved in art psychotherapy.