Roberts Cross Research Articles

잡음 종류와 잡음 제거방식에 따른 영상의 윤곽선 검출 비교

In this paper, we show comparison results of edge detection of images that have additive gaussian noise or salt and pepper noise by using various techniques of noise removal such as filtering, morphology and deep learning based ones. In particular, this present work provides comparison results of noise removal by using gaussian filter, open and close operations of morphology and auto-encoder model followed by carrying out edge detection. Robert cross, Sobel, Prewitt and Canny detectors are used for edge detection of the images with noise removal. Experimental results show that noise removal results are different with characteristics of noise and techniques applied for noise removal. In addition, deep learning based technique, auto-encoder does not always shows superior results of noise removal, particularly in the case of existence of salt-pepper noise. In the experiments, gaussian noise or salt-pepper noise is used and peak signal noise ratio (PSNR) is used for quantitative comparison and the results of edge detection is qualitatively compared from visual perspective.

Comparison of Gradient-Based Edge Detectors Applied on Mammograms

Breast cancer is one of the most common types of cancer amongst women, but it is also one of the most frequently cured cancers. Because of this, early detection is crucial, and this can be done through mammography screening. With the increasing need of an automated interpretation system, a lot of methods have been proposed so far and, regardless of the algorithms, they all share a step: pre-processing. That is, identifying the image orientation, detecting the breast and eliminating irrelevant parts.
 This paper aims to describe, analyze, compare and evaluate six of the most commonly used edge detection operators: Sobel, Roberts Cross, Prewitt, Farid and Simoncelli, Scharr and Canny. We detail the algorithms, their implementations and the metrics used for evaluation and continue by comparing the operators both visually and numerically, finally concluding that Canny best suit our needs.

Classification of flower images using SVM method through the colour, texture and shape using Histogram, Haar Wavelet and Robert Cross methods

Flowers are one of the plants that offer a beauty that makes the environment more beautiful and attractive. Not only a decoration, but flowers are also used as cut flowers, sowing flowers and herbal medicine. flowers that grow in Indonesia have two forms, namely the form of a flower and a bunch. In the classification of flower characteristics taken from the flower, images are characteristics of colour, texture and shape. The purpose of this system design is to make a classification of flowers that grow in Indonesia that have different colour, texture and shape characters using the Histogram, Haar Wavelet and Robert Cross methods to get the value of features to be made vector and used on SVM method to determine the types of flowers. SVM is a classifier that has the advantage of being able to process high-dimensional data, without eliminating significant performance degradation. From the experiment of this Indonesian flower classification application, the accuracy of classification success results in the test interest of 81.67% by using the colour, texture and shape features of the extraction results with the Histogram, Haar Wavelet and Robert Cross methods and classified by the SVM method with Linear, Polynomial kernel and RBF.

Hybrid Binary-Unary Hardware Accelerator

Stream-based computing such as stochastic computing has been used in recent years to create designs with significantly smaller area by harnessing unary encoding of data. However, the area saving comes at an exponential price in latency, making the area × delay cost unattractive. In this article, we present a novel method which uses a hybrid binary / unary representation to perform computations. We first divide the input range into a few sub-regions, perform unary computations on each sub-region individually, and finally pack the outputs of all sub-regions back to compact binary. Moreover, we propose a synthesis methodology and a regression model to predict an optimal or close-to-optimal design in the design space. To the best of our knowledge, we are the first to show a scalable method based on parallel bit-stream data representation that can beat conventional binary in terms of a real cost, i.e., area × delay and energy consumption in almost all functions that we tried at resolutions of 8-, 10-, and 12-bits. Our method outperforms the binary, stochastic, and fully unary methods on a number of functions, especially low-cost binary CORDIC-based functions, and on a common edge detection algorithm on FPGA and in ASIC implementation. In terms of area × delay cost, our {on FPGA, in ASIC} cost is on average only { $4.72\%$ 4 . 72 % , $24.36\%$ 24 . 36 % } and { $20.16\%$ 20 . 16 % , $60.12\%$ 60 . 12 % } of the parallel binary pipeline implementation at 8- and 10-bit resolution, respectively. These numbers are 2–3 orders of magnitude better than the results of traditional stochastic methods. Our method is not competitive with the parallel CORDIC-based pipeline binary method for high-resolution (12-bit), highly oscillating functions such as $\sin (15 x)$ sin ( 15 x ) . However, for complex functions like $gamma$ g a m m a function, the proposed method can beat any other methods in terms of area × delay, throughput, latency, and energy per sample costs. To implement the Roberts cross edge detection algorithm, the proposed method takes 5.7 and 39.45 percent of the area × delay cost of FPGA and ASIC implementation of the binary method, respectively. In terms of energy efficiency for FPGA implementation, our method uses only 8.4, 12.7, and 27.7 percent of the energy per sample usage of serial binary implementations at 8-, 10-, and 12-bit resolutions, respectively. These numbers change to 23.9, 38.54, and 99.3 percent compared to parallel binary implementations.

Multi-feature fusion tree trunk detection and orchard mobile robot localization using camera/ultrasonic sensors

In a semi-structured orange orchard, multi-tree trunk detection is an effective method for mobile robot localization. However, because of the complex background of the natural orchard environment, dwarf orange tree trunks are easy to misrecognize. In this paper, we present a novel tree trunk detection method based onmultiplecameras and ultrasonicsensors integration technology. These devices are integrated intoa single organicmechanical structure that can rotate to detect the surrounding orchard environment such that they can reduce the non-detectionzone. Multi-feature fusion will be used in this study. First, histograms of oriented gradient (HOG) and support vector machine (SVM) are used to train an initial tree trunk classifier. Next, the gray scale histogram features of the tree trunk and non-trunk images are extracted to optimize the classifier. Finally, the Roberts cross edge detector is used to extract the trunk’s gradient histogram features, which will improve the recognition accuracy of the classifier. The orange tree trunk recognition experiments exhibited a recall rate and accuracy of 92.14% and 95.49%, respectively. On this basis, ultrasonic sensors are used to get the location data of the trunks and a moving average filter is used to reduce the error of mobile robot localization. The experiment showed that the average localization error was approximately 62 mm (2.5%), and the robot moved stably and precisely along the road of the semi-structured orange orchard.

The Impact of the Implementation of Edge Detection Methods on the Accuracy of Automatic Voltage Reading

Abstract The article presents the impact of the edge detection method in the image analysis on the reading accuracy of the measured value. In order to ensure the automatic reading of the measured value by an analog meter, a standard webcam and the LabVIEW programme were applied. NI Vision Development tools were used. The Hough transform was used to detect the indicator. The programme output was compared during the application of several methods of edge detection. Those included: the Prewitt operator, the Roberts cross, the Sobel operator and the Canny edge detector. The image analysis was made for an analog meter indicator with the above-mentioned methods, and the results of that analysis were compared with each other and presented.

Surface Quality Detection of Welding Nuts Based on Machine Vision

Welding nuts are being used widely in automotive industry as threaded fasteners, its security and reliability requests are increasingly high. Accurate and quick detection results for surface quality can be obtained by using machine vision. Image edge detection by Canny operator has stronger acclimatization in anti-jamming and accurate edge localization. In order to suppress noise in maximum, an improved method is put forward to calculate the gradient of Canny operator, introducing Robert cross gradient in 3×3 neighborhood when calculating the gradient magnitude in finite difference method. The experimental results show that the improved Canny operator makes more effectively on the surface detection of welding nuts.

Likewise - radar fractional-order edge detector

In this paper a new likewise – radar fractional order edge detector is presented. Proposed edge detector is compared with well-known edge detectors like Sobel operator, Robert cross and with method based on fractional-order derivatives. Based on fractional differentiation a mask for edge detection is created. The main idea of presented algorithm is it works in similar way to radars, namely mask is rotating through 180 degrees in each pixel of the image.

Better connected

Informal networks are key to idea-sharing, argue Mark Fishman, Robert Cross and Brigitta Tadmor.

Implementation of edge detection algorithms to characterize magnetic micropillars patterned by X-ray lithography

The array of SU-8 photoresist pillars (10 ´ 10 ´ 50 µm) on a copper substrate was patterned by X-ray lithography using a synchrotron source. Flat cobalt films can then be sputter-deposited on the chemically stable and mechanically hardened SU-8 pillars in spite of geometry distortion and pattern collapse in some regions. Since any deviations from the pattern affect magnetic properties of the structure, images of these micropillars obtained from an optical microscope and a scanning electron microscope (SEM) were inspected using five different edge detection algorithms. The Canny and Laplacian of Gaussian (LoG) operators can detect all cross sections of micropillars, but noise points and lines were also included. The outputs from image processing by the Prewitt and Sobel operators yielded lower noise, but suffered from discontinuity, especially in the case of tilt angled SEM images. The Roberts cross edge detector had a weakest response to edges of the pattern under test. The 3D nature of the micropillars is an origin of low-contrast edge and background noise in the images. Key words: X-ray lithography, SU-8 photoresist, high-aspect-ratio microstructure, image processing, edge detection.

Take advantage of uncertainty: Play for position as the economy rebounds

On 6–7 October 2009, the fifth annual Revenue Management and Price Optimization conference was held at the Georgia Institute of Technology. The conference explored ways that firms are using to survive the current economic downturn and to position themselves to quickly recover as the economy rebounds. Several strategies for building a strong business case to secure funding for projects emerged from the discussions. In addition, the critical role of communication across divisions was emphasized. Strong communication helps create support for new projects, enables different divisions to focus on a common set of objectives and understand how their decisions affect key performance metrics, and facilitates the transfer of ideas and best practices. This article summarizes key discussions that emerged from the conference and highlights the experiences of three companies portrayed in keynote addresses given by Robert Cross, Chairman and CEO of Revenue Analytics; John Peyton, Senior Vice President of North American Operations at Starwood Hotels and Resorts; and Doug Bippert, Vice President of Business Acceleration at the Coca-Cola Company.

Determination of Twist Gray Matter and Some Dark Features of Human Brain in

In this article we describe automatic image processing method for determination twist gray matter and some dark features of human brain in computer tomography images. Suggested algorithm of the method used six different functions for image processing. The first was noise-reducing function, which made possible to apply ”Roberts Cross” and matching functions. Threshold function separated the features of components of images into two values – black and white. In this way the amount of information for further processing was reduced. Dilation and erosion functions performed human brain twist matter selection and elimination of some dark images features that could be the ischemic stroke features. In Vilnius University Hospital ”Santariskės” 60 automatically processed computer tomography images of human brain were evaluated by experts in radiology. More than 90 % of processed images were evaluated in marks 10 and 9 using ten point’s evaluation system. Ill. 13, bibl. 8 (in Lithuanian; summaries in Lithuanian, English and Russian).

Reviews

Journal Article Reviews Get access Vita Sackville-West: A Bibliography. By ROBERT CROSS and ANN RAVENSCROFT-HULME. Foreword by NIGEL NICHOLSON. Winchester: St Paul's Bibliographies; New Castle, DE: Oak Knoll Press. 1999. xiv + 306 pp. £50.00. ISBN I 873040 26 I. STEPHEN TABOR STEPHEN TABOR Van Nuys, California Search for other works by this author on: Oxford Academic Google Scholar The Library, Volume 2, Issue 3, September 2001, Pages 302–304, https://doi.org/10.1093/library/2.3.302 Published: 01 September 2001

Books: Promise, Premise, Performance: Five Perspectives on the State of Higher Education

Abstract Street of Dreams: The Nature and Legacy of the 1960s by Douglas M. Knight. Durham, NC: Duke University Press, 1989. Reviewed by Robert Cross. The University: And Owner's Manual by Henry Rosovsky. New York: W. W. Norton & Company, 1990. Reviewed by Robert Cross. How Harvard Rules: Reason in the Service of Empire edited by john Trumpbour. Boston: South End Press, 1989. Reviewed by Robert Cross. Strainght Shooting: What's Wrong with America, and How to Fix it by John Silber. New York: Harper & Row. 1989. Reviewed by Robert Cross. The Moral Collapse of the University: Professionalism, Purity, and Allienation by Bruce wilshire, Albany: State University of New York Press, 1990. Reviewed by Robert Cross.

The effect of spatial discretization on the magnitude and direction response of simple differential edge operators on a step edge

For a unit step edge, we calculate the gradient magnitude and direction reported by various simple differential edge operators as a function of the edge's actual orientation and offset with respect to the pixel grid. To be consistent with previous work (of Abdou and Pratt) we have initially chosen to analyse (among others) the Sobel, Prewitt, and Roberts Cross operators, using a digitization model in which the pixels have uniform square receptive fields that tesselate the image plane. Our quantitative results provide insights into the behavior of these commonly used operators, insights that can guide their proper application in problems of image understanding and robot vision. We also suggest novel techniques for improving the performance of these operators.

Edge detection using charge analogy

In this paper a technique based on a charge analogy is presented for the design of edge detectors in various sizes. Using this analogy, an extended version of the Roberts cross operator is derived. The results of an edge-detection experiment on two digital pictures are also presented.

Prelude To ‘Americanism’: The New York Accademia and Clerical Radicalism in the Late Nineteenth Century

The Americanist crisis in the last decade of the nineteenth century climaxed the attempt of a group of liberal prelates and their associates to adapt Roman Catholicism to democratic institutions and values. Almost twenty years ago Robert Cross put this complex movement within the context of a growing American Catholic liberalism in the postbellum period. The full dimensions of that liberalism are still coming into focus as archival materials and unpublished sources become more available to the historian. The recent discovery of a remarkable association of New York priests shows another facet of the Americanist controversy that better enables us to appreciate the peculiar lines that the episcopal struggle assumed.

No title] - Results of Thyroid Feeding in Insanity. By Robert Cross, M.B., C.M., Assistant Medical Officer, Midlothian and Peebles Asylum. (Reprinted from the Edinburgh Medical Journal, Nov., 1897.)

No title] - Results of Thyroid Feeding in Insanity. By Robert Cross, M.B., C.M., Assistant Medical Officer, Midlothian and Peebles Asylum. (Reprinted from the <i>Edinburgh Medical Journal,</i> Nov., 1897.)