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Edge Detection (edge + detection)

Distribution by Scientific Domains

Engineering	30%

Selected Abstracts

Auxetic compliant flexible PU foams: static and dynamic properties

PHYSICA STATUS SOLIDI (B) BASIC SOLID STATE PHYSICS, Issue 3 2005
F. Scarpa
Abstract The paper describes the manufacturing and tensile testing of auxetic (negative Poisson's ratio) thermoplastic polyurethane foams, both under constant strain rate and sinusoidal excitation. The foams are produced from conventional flexible polyurethane basis following a manufacturing route developed in previous works. The Poisson's ratio behaviour over tensile strain has been analyzed using an Image Data processing technique based on Edge Detection from digital images recorded during quasi-static tensile test. The samples have been subjected to tensile and compressive tests at quasi-static and constant strain-rate values (up to 12 s,1). Analogous tests have been performed over iso-volumetric foams samples, i.e., foams subjected to the same volumetric compression of the auxetic ones, exhibiting a near zero Poisson's ratio behaviour. The auxetic and non-auxetic foams have been also tested under sinusoidal cycling load up to 10 Hz, with maximum pre-strain applied of 12%. The hysteresis of the cycling loading curve has been measured to determine the damping hysteretic loss factor for the various foams. The measurements indicate that auxetic foams have increased damping loss factor of 20% compared to the conventional foams. The energy dissipation is particularly relevant in the tensile segment of the curve, with effects given by the pre-strain level imposed on the samples. (© 2005 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source]

Interval type-2 fuzzy logic for edges detection in digital images

INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 11 2009
Olivia Mendoza
Edges detection in a digital image is the first step in an image recognition system. In this paper, we show an efficient edges detector using an interval type-2 fuzzy inference system (FIS-2). The FIS-2 uses as input the original images after applying Sobel filters and attenuation filters, then the fuzzy rules infer normalized values for the edges images, especially useful to enhance the performance of neural networks. To illustrate the results, we built frequency histograms of some images and compare the results of the FIS-2 edge's detector with the gradient magnitude method and a type-1 fuzzy inference system (FIS-1). The FIS-2 results are better than the gradient magnitude and FIS-1, because the edges preserve more detail of the original images, and the backgrounds are more homogeneous than with FIS-1 and the gradient's magnitude method. © 2009 Wiley Periodicals, Inc. [source]

Object detection using straight line matching in ,-, space

ELECTRONICS & COMMUNICATIONS IN JAPAN, Issue 3 2010
Taisei Okuzono
Abstract The contours of many industrial parts contain straight lines and the positions of the lines are therefore useful information for object detection. This paper presents a matching technique for straight lines. The method consists of ,-matching, ,-matching, and pose estimation. Any lines in 2D space are represented with parameters , and , by the Hough transform. In order to find the corresponding lines in a model and a scene, the , and , values are evaluated in ,-matching and ,-matching. When an object is translated and rotated, the contour lines of the object are also transferred and the , values of the lines are merely shifted by the rotation angle in the ,-, space. Thus, the relative positions of the , values are invariant. In ,-matching, the corresponding lines of the model and the scene are selected so that the relative , values of the corresponding lines are nearly equal. In ,-matching, the corresponding lines are evaluated further by computing the deviations of their , values. Finally, the transfer parameters of the selected pairs are estimated in pose estimation. The experiments show that this technique is robust to rotation, occlusion, and scaling of the objects. We also discuss the computation time, in which the preprocess such as edge detection and the Hough transform takes much of the time. © 2010 Wiley Periodicals, Inc. Electron Comm Jpn, 93(3): 34,41, 2010; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecj.10176 [source]

Brain responses to auditory and visual stimulus offset: Shared representations of temporal edges

HUMAN BRAIN MAPPING, Issue 3 2009
Marcus Herdener
Abstract Edges are crucial for the formation of coherent objects from sequential sensory inputs within a single modality. Moreover, temporally coincident boundaries of perceptual objects across different sensory modalities facilitate crossmodal integration. Here, we used functional magnetic resonance imaging in order to examine the neural basis of temporal edge detection across modalities. Onsets of sensory inputs are not only related to the detection of an edge but also to the processing of novel sensory inputs. Thus, we used transitions from input to rest (offsets) as convenient stimuli for studying the neural underpinnings of visual and acoustic edge detection per se. We found, besides modality-specific patterns, shared visual and auditory offset-related activity in the superior temporal sulcus and insula of the right hemisphere. Our data suggest that right hemispheric regions known to be involved in multisensory processing are crucial for detection of edges in the temporal domain across both visual and auditory modalities. This operation is likely to facilitate cross-modal object feature binding based on temporal coincidence. Hum Brain Mapp, 2009. © 2008 Wiley-Liss, Inc. [source]

An efficient adaptive algorithm for edge detection based on the likelihood ratio test

INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 4 2002
A. De Santis
Abstract The edge detection problem in blurred and noisy 2-D signals is dealt with. An adaptive signal processing algorithm is proposed which marks edge points according to an hypothesis test which compares the likelihoods of two models describing the local signal behaviour in the two cases of absence/presence of an edge. The two models are identified by a regularized least squares estimation algorithm, obtaining a numerically efficient procedure, quite robust with respect to additive noise and blurr perturbation. No global thresholding or data prefiltering is required. Copyright © 2002 John Wiley & Sons, Ltd. [source]

Automatic classification of protein crystallization images using a curve-tracking algorithm

JOURNAL OF APPLIED CRYSTALLOGRAPHY, Issue 2 2004
Marshall Bern
An algorithm for automatic classification of protein crystallization images acquired from a high-throughput vapor-diffusion system is described. The classifier uses edge detection followed by dynamic-programming curve tracking to determine the drop boundary; this technique optimizes a scoring function that incorporates roundness, smoothness and gradient intensity. The classifier focuses on the most promising region in the drop and computes a number of statistical features, including some derived from the Hough transform and from curve tracking. The five classes of images are `Empty', `Clear', `Precipitate', `Microcrystal Hit' and `Crystal'. On test data, the classifier gives about 12% false negatives (true crystals called `Empty', `Clear' or `Precipitate') and about 14% false positives (true clears or precipitates called `Crystal' or `Microcrystal Hit'). [source]

Optimal Representative Blocks for the Efficient Tracking of a Moving Object

JOURNAL OF FIELD ROBOTICS (FORMERLY JOURNAL OF ROBOTIC SYSTEMS), Issue 3 2004
SangJoo Kim
Optimal representative blocks are proposed for an efficient tracking of a moving object and it is verified experimentally by using a mobile robot with a pan-tilt camera. The key idea comes from the fact that when the image size of a moving object is shrunk in an image frame according to the distance between the camera of mobile robot and the moving object, the tracking performance of a moving object can be improved by shrinking the size of representative blocks according to the object image size. Motion estimation using edge detection (ED) and block-matching algorithm (BMA) are often used in the case of moving object tracking by vision sensors. However, these methods often miss the real-time vision data since these schemes suffer from the heavy computational load. To overcome this problem and to improve the tracking performance, the optimal representative block that can reduce a lot of data to be computed is defined and optimized by changing the size of the representative block according to the size of object in the image frame. The proposed algorithm is verified experimentally by using a mobile robot with a two degree-of-freedom active camera. © 2004 Wiley Periodicals, Inc. [source]

Decorrugation, edge detection, and modelling of total field magnetic observations from a historic town site, Yellowstone National Park, USA

ARCHAEOLOGICAL PROSPECTION, Issue 1 2010
Steven D. Sheriff
Abstract Cinnabar, Montana is a historic town site and railroad depot near the northern edge of Yellowstone National Park and was inhabited between 1883 and 1903. Remains of foundations and old photographs help determine the area of the town, but the south and east limits are unknown. We acquired total field magnetic intensity data to help determine the full extent of the town. Randomly distributed ferrous magnetic sources on the surface and typical noise associated with acquisition complicate the signal. To separate signal and noise we applied filtering and edge detection techniques common in the aeromagnetic industry to our data. Regional removal, decorrugation, upward continuation, and edge detection successfully separated signal and noise. Following filtering, we extracted two larger anomalies from the data set. For those two anomalies, we estimated the edges of their causative sources by calculating the maxima in the horizontal gradient of their anomalies and by inverse modelling those sources; both methods yield similar results. An archaeological test unit excavation within one of the anomalies clearly indicates the remains of buried domestic features, the foundation to a house or other building associated with the late nineteenth to early twentieth century use of Cinnabar. Thus the southeast extent of Cinnabar is greater than previously thought. The lack of surface indicators or adequate historic photography precluded the identification of this buried feature without the aid of the magnetic study. Copyright © 2009 John Wiley & Sons, Ltd. [source]