An efficient method for finding intersections of many manifolds with application to patch based image processing

2013 ◽  
Author(s):  
Yevgen Matviychuk ◽  
Shannon M. Hughes
Keyword(s):  
Image Processing ◽  
Efficient Method

An Efficient Image-Based Method for Detection of Fastener on Railway

2011 ◽  
Vol 346 ◽  
pp. 731-737 ◽  
Author(s):  
Jin Feng Yang ◽  
Man Hua Liu ◽  
Hui Zhao ◽  
Wei Tao
Keyword(s):  
Image Processing ◽  
Efficient Method ◽  
Template Matching ◽  
Detection Method ◽  
Experimental Results ◽  
Feature Descriptor ◽  
Complex Environment ◽  
Computation Efficiency ◽  
The Status ◽  
Direction Field

This paper presents an efficient method to detect the fastener based on the technologies of image processing and optical detection. As feature descriptor, the Direction Field of fastener image is computed for template matching. This fastener detection method can be used to determine the status of fastener on the corresponding track, i.e., whether the fastener is on the track or missing. Experimental results are presented to show that the proposed method is computation efficiency and is robust for fastener detection in complex environment.

Efficient Method for Image Indexing in Medical Application

2011 ◽  
pp. 257-264
Author(s):  
Richard Chbeir
Keyword(s):  
Image Processing ◽  
Data Processing ◽  
Image Retrieval ◽  
Efficient Method ◽  
Medical Application ◽  
Image Indexing ◽  
Exact Matching ◽  
Standard Data ◽  
Image Processing Algorithms ◽  
Processing Algorithms

In last two decades, image retrieval has seen a growth of interests in several domains. As a result, a lot of work has been done in order to integrate it in the standard data processing environments (Rui, Huang, & Chang, 1999; Smeulders, Gevers, & Kersten, 1998; Yoshitaka & Ichikawa, 1999). To retrieve images, different methods have been proposed in the literature (Chang & Jungert, 1997; Guttman, 1984; Lin, Jagadish, & Faloutsos, 1994). These methods can be grouped into two major approaches: metadata-based and content-based approaches. The metadata-based approach uses alphanumeric attributes and traditional techniques to describe the context and/or the content of the image such as title, author name, date, and so on. The content-based approach uses image processing algorithms to extract low-level features of images such as colors, textures, and shapes. Image retrieval using these features is done by methods of similarity and hence is a non-exact matching.

scholarly journals A More Flexible Approach to Utilizing Depth Cameras for Hand andTouch Interaction

2012 ◽  
Vol 11 (3) ◽  
pp. 53-57 ◽  
Author(s):  
Thomas Butkiewicz
Keyword(s):  
Image Processing ◽  
Efficient Method ◽  
Low Cost ◽  
Kinect Sensor ◽  
Processing Methods ◽  
Flexible Approach ◽  
Depth Cameras ◽  
Depth Images ◽  
Surface Reflectivity ◽  
Gestural Input

Many researchers have utilized depth cameras for tracking user's hands to implement various interaction methods, such as touch-sensitive displays and gestural input. With the recent introduction of Microsoft's low-cost Kinect sensor, there is increased interest in this strategy. However, a review of the existing literature on these systems suggests that the majority suffer from similar limitations due to the image processing methods used to extract, segment, and relate the user's body to the environment/display. This paper presents a simple, efficient method for extracting interactions from depth images that is more flexible in terms of sensor placement, display orientation, and dependency on surface reflectivity.

scholarly journals Security Based Brain Tumor Classification using Image Fusion

2020 ◽  
Vol 9 (7) ◽  
pp. 1315-1318
Keyword(s):  
Image Processing ◽  
Brain Tumor ◽  
Image Fusion ◽  
Data Storage ◽  
Efficient Method ◽  
Medical Images ◽  
Tumor Classification

Today, the use of medical images is often complicated for diagnosis process and planning of treatment. The major challenge in image processing and fusion includes data mismatching, data storage issues and security constraints. Although several techniques are being used for image processing, they lack in security parameters. Our objective is to provide an efficient method for image fusion techniques along with the security paradigms. In order to provide security, encryption standards are used. The results of improved framework give better performance and quality over existing methods in terms of security, database information, and fusion factor.

scholarly journals Low Complexity Fluctuation Measurement in Image Processing Considering Order

2018 ◽  
Vol 8 (6) ◽  
pp. 4253
Author(s):  
Tareq Khan
Keyword(s):  
Image Processing ◽  
Standard Deviation ◽  
Efficient Method ◽  
Low Complexity ◽  
Fluctuation Measurement

The standard deviation can measure the spread out of a set of numbers and entropy can measure the randomness. However, they do not consider the order of the numbers. This can lead to misleading results where the order of the numbers is vital. An image is a set of numbers (i.e. pixel values) that is sensitive to order. In this paper, a low complexity and efficient method for measuring the fluctuation is proposed considering the order of the numbers. The proposed method sums up the changes of consecutive numbers and can be used in image processing applications. Simulation shows that the proposed method is 8 to 33 times faster than other related works.

A NOVEL NOISE REMOVAL METHOD BASED ON FRACTIONAL ANISOTROPIC DIFFUSION AND SUBPIXEL APPROACH

2011 ◽  
Vol 07 (01) ◽  
pp. 173-185 ◽  
Author(s):  
YINGTAO ZHANG ◽  
H. D. CHENG ◽  
YANGQUAN CHEN ◽  
JIANHUA HUANG
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Efficient Method ◽  
Anisotropic Diffusion ◽  
Signal To Noise Ratio ◽  
Noise Removal ◽  
Nonlinear Pde ◽  
Signal To Noise ◽  
Partial Difference ◽  
Better Than

Partial differential equations (PDE) have been successfully and widely applied to image processing and computer vision. Anisotropic diffusion is an approach to remove noise based on nonlinear PDE. Many anisotropic methods have been studied; however, they suffer two major drawbacks: blurring and staircasing effects degrading the performance of noise removal filters. To overcome such problems, in this paper, a novel and efficient method for image denoising based on fractional-order anisotropic diffusion and subpixel approach is proposed. Numerical computation is implemented by using the subpixel fractional partial difference (SFPD) approach to increase the flexibility and accuracy. The experimental results demonstrate that the proposed approach can achieve higher signal-to-noise ratio (SNR) and its performance is much better than that of the existing filters.

Some comments about observations and image processing of comet 29P/Schwassmann-Wachmann 1

1999 ◽  
Vol 173 ◽  
pp. 243-248
Author(s):  
D. Kubáček ◽  
A. Galád ◽  
A. Pravda
Keyword(s):  
Image Processing ◽  
Large Scale ◽  
Harvard College ◽  
Oak Ridge ◽  
Large Scale Structures ◽  
Short Period Comet ◽  
Short Period ◽  
Scale Structures ◽  
Harvard College Observatory ◽  
Period Comet

AbstractUnusual short-period comet 29P/Schwassmann-Wachmann 1 inspired many observers to explain its unpredictable outbursts. In this paper large scale structures and features from the inner part of the coma in time periods around outbursts are studied. CCD images were taken at Whipple Observatory, Mt. Hopkins, in 1989 and at Astronomical Observatory, Modra, from 1995 to 1998. Photographic plates of the comet were taken at Harvard College Observatory, Oak Ridge, from 1974 to 1982. The latter were digitized at first to apply the same techniques of image processing for optimizing the visibility of features in the coma during outbursts. Outbursts and coma structures show various shapes.

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