Image Partitioning on Spiral Architecture

Author(s):  
Qiang Wu ◽  
Xiangjian He

Spiral Architecture is a relatively new and powerful approach to image processing. It contains very useful geometric and algebraic properties. Based on the abundant research achievements in the past decades, it is shown that Spiral Architecture will play an increasingly important role in image processing and computer vision. This chapter presents a significant application of Spiral Architecture for distributed image processing. It demonstrates the impressive characteristics of spiral architecture for high performance image processing. The proposed method tackles several challenging practical problems during the implementation. The proposed method reduces the data communication between the processing nodes and is configurable. Moreover, the proposed partitioning scheme has a consistent approach: after image partitioning each sub-image should be a representative of the original one without changing the basic object, which is important to the related image processing operations.

Author(s):  
Lei Xu ◽  
Erkki Oja

Proposed in 1962, the Hough transform (HT) has been widely applied and investigated for detecting curves, shapes, and motions in the fields of image processing and computer vision. However, the HT has several shortcomings, including high computational cost, low detection accuracy, vulnerability to noise, and possibility of missing objects. Many efforts target at solving some of the problems for decades, while the key idea remains more or less the same. Proposed in 1989 and further developed thereafter, the Randomized Hough Transform (RHT) manages to considerably overcome these shortcomings via innovations on the fundamental mechanisms, with random sampling in place of pixel scanning, converging mapping in place of diverging mapping, and dynamic storage in place of accumulation array. This article will provides an overview on advances and applications of RHT in the past one and half decades.


Author(s):  
Dr. Kavita R. Singh ◽  
◽  
Ruchika Sinhal ◽  
Ravi Wasalwar ◽  
Gupta Dr. K. O ◽  
...  

With the growing advancements and development in the field of digital image processing and computer vision, an individual’s heart pulse can be extracted from the human skin surfaces. This method is termed as remote photoplethysmography (rPPG). The method can be applied from the video recorded from the consumer-based mobile camera also. In this paper, the work presented has mainly twofold goals. Firstly to develop a fruitful yet simple rPPG algorithm that should be simple for any individual to understand and implement that will increase the understanding of the rPPG subject. Secondly, to compare the algorithm designed for the RGB color model with the state-of-art rPPG algorithms developed and presented in the literature. And finally, we present the comparative analysis of rPPG algorithms reported in the literature with our proposed rPPG algorithm which is simple and has demonstrated comparably high performance for the green channel as compared to other algorithms.


Author(s):  
Vorapoj Patanavijit ◽  
Kornkamol Thakulsukanant

<p>In the past two decades, the SPN (salt and pepper noise) suppressing method is worldwide interested researches on computer vision and image processing hence many SPN suppressing methods have been proposed. In general, the primary goal of SPN removal method is the suppressing of SPN in digital images thereby one of the recent effective and powerful SPN suppressing methods is a new switching-based median filtering (NSMF), which is innovated for suppressing high density SPN. Consequently, this paper thoroughly examines its efficiency and constrain of a new switching-based median filtering when this filter is used for contaminated image, which is synthesized by SPN and RVIN (random-value impulsive noise). In these simulations, six well-known images (Lena, Mobile, Pepper, Pentagon, Girl, Resolution) with two impulsive noise classes (SPN and RVIN) are used for measuring the its efficiency and constrain. An evaluation of the efficiency is conducted with many previous methods in forms of subjective and objective indicators.</p>


Author(s):  
V. Tournadre ◽  
C. Labarta ◽  
P. Megard ◽  
A. Garric ◽  
E. Saubestre ◽  
...  

CFEETK, the French-Egyptian Center for the Study of the Temples of Karnak, is celebrating this year the 50<sup>th</sup> anniversary of its foundation. As a multicultural and transdisciplinary research center, it has always been a playground for testing emerging technologies applied to various fields. The raise of automatic computer vision algorithms is an interesting topic, as it allows nonexperts to provide high value results. This article presents the evolution in measurement experiments in the past 50 years, and it describes how cameras are used today. Ultimately, it aims to set the trends of the upcoming projects and it discusses how image processing could contribute further to the study and the conservation of the cultural heritage.


Author(s):  
P. S. P. WANG ◽  
JIANWEI YANG

Edges are prominent features in images. The detection and analysis of edges are key issues in image processing, computer vision and pattern recognition. Wavelet provides a powerful tool to analyze the local regularity of signals. Wavelet transform has been successfully applied to the analysis and detection of edges. A great number of wavelet-based edge detection methods have been proposed over the past years. The objective of this paper is to give a brief review of these methods, and encourage the research of this topic. In practice, an image is usually of multistructure edge, the identification of different edges, such as steps, curves and junctions play an important role in pattern recognition. In this paper, more attention is paid on the identification of different types of edges. We present the main idea and the properties of these methods.


Author(s):  
John Mansfield

Advances in camera technology and digital instrument control have meant that in modern microscopy, the image that was, in the past, typically recorded on a piece of film is now recorded directly into a computer. The transfer of the analog image seen in the microscope to the digitized picture in the computer does not mean, however, that the problems associated with recording images, analyzing them, and preparing them for publication, have all miraculously been solved. The steps involved in the recording an image to film remain largely intact in the digital world. The image is recorded, prepared for measurement in some way, analyzed, and then prepared for presentation.Digital image acquisition schemes are largely the realm of the microscope manufacturers, however, there are also a multitude of “homemade” acquisition systems in microscope laboratories around the world. It is not the mission of this tutorial to deal with the various acquisition systems, but rather to introduce the novice user to rudimentary image processing and measurement.


2018 ◽  
Vol 1 (2) ◽  
pp. 17-23
Author(s):  
Takialddin Al Smadi

This survey outlines the use of computer vision in Image and video processing in multidisciplinary applications; either in academia or industry, which are active in this field.The scope of this paper covers the theoretical and practical aspects in image and video processing in addition of computer vision, from essential research to evolution of application.In this paper a various subjects of image processing and computer vision will be demonstrated ,these subjects are spanned from the evolution of mobile augmented reality (MAR) applications, to augmented reality under 3D modeling and real time depth imaging, video processing algorithms will be discussed to get higher depth video compression, beside that in the field of mobile platform an automatic computer vision system for citrus fruit has been implemented ,where the Bayesian classification with Boundary Growing to detect the text in the video scene. Also the paper illustrates the usability of the handed interactive method to the portable projector based on augmented reality.   © 2018 JASET, International Scholars and Researchers Association


2012 ◽  
Vol 17 (4) ◽  
pp. 207-216 ◽  
Author(s):  
Magdalena Szymczyk ◽  
Piotr Szymczyk

Abstract The MATLAB is a technical computing language used in a variety of fields, such as control systems, image and signal processing, visualization, financial process simulations in an easy-to-use environment. MATLAB offers "toolboxes" which are specialized libraries for variety scientific domains, and a simplified interface to high-performance libraries (LAPACK, BLAS, FFTW too). Now MATLAB is enriched by the possibility of parallel computing with the Parallel Computing ToolboxTM and MATLAB Distributed Computing ServerTM. In this article we present some of the key features of MATLAB parallel applications focused on using GPU processors for image processing.


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