CoLFDImaP: A web‐based tool for teaching of FPGA‐based digital image processing in undergraduate courses

García, Iván A.; Guzmán‐Ramírez, Enrique; Pacheco, Carla

doi:10.1002/cae.21581

Cited by 17 publications

(11 citation statements)

References 60 publications

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“…However, these studies usually deal with image processing procedures or they are prepared for understanding the reconfigurable logic tool and debugging the reconfigurable logic implementations. Various pedagogical frameworks such as project based learning, e‐learning, distance learning, collaborative learning, and learning by doing are used to teach programmable logic devices in the literature . One of these pedagogical frameworks is the problem based learning approach.…”

Section: The Training Course Detailsmentioning

confidence: 99%

“…To conduct a survey about the training process is frequently preferred method in the literature to learn the ideas of the trainees . In this 3‐week training process, the students have answered a survey in order to be able to assess the contribution of the subject to their modeling, simulation and implementation skills at the end of the second week.…”

Section: The Training Course Detailsmentioning

confidence: 99%

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Modeling, simulation, and implementation issues of CPGs for neuromorphic engineering applications

Korkmaz

Öztürk

Kılıç

2018

Comp Applic In Engineering

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Neuromorphic engineering is a discipline used to develop hardware, which can mimic the characteristics and abilities of biological systems by investigating their physiological structures and data transfer mechanisms. The recent studies about the neuromorphic systems mostly consist of robotic applications whose designs are inspired by Central Pattern Generators (CPGs). CPGs are special neural networks which can produce coordinated rhythmic activity patterns and these rhythmic movements are modeled mathematically, tested with simulation programs and verified by hardware implementations. A reconfigurable hardware platform (Field Programmable Gate Array “FPGA”) is compatible with numerical simulation tools, allows software control over hardware, has a user‐friendly interface and allows real time modifications. Thus, recently, it is preferred in CPG based robotic applications. In this study, the details of the modeling, simulation and implementation stages of several CPG structures are introduced by using a digital reconfigurable hardware platform. In order to show the conceptual learning achievements of these stages and to assess the contribution to the modeling, simulation and implementation skills of the students, a training course has been planned for the undergraduate students at Erciyes University. This process has been held in an educative manner supported by a survey and an experimental examination, so that this training course has been evaluated by the trainees in terms of the advantage, practicality, and challenge.

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Section: The Training Course Detailsmentioning

confidence: 99%

Section: The Training Course Detailsmentioning

confidence: 99%

Modeling, simulation, and implementation issues of CPGs for neuromorphic engineering applications

Korkmaz

Öztürk

Kılıç

2018

Comp Applic In Engineering

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“…We observed that one of the main findings was that the combination of PBL with the proposed FPGA‐based system for teaching, modeling, and implementing the image processing algorithms can improve student performance. Later, as a further improvement, we modified the pedagogical approach by introducing the web‐based real‐time experimentation under a collaborative environment in the creation of the Collaborative Lab for FPGA‐based Digital Image Processing , which has been applied as a teaching aid in an undergraduate course using digital image processing and FPGA technologies .…”

Section: The Fpga Role In Engineering Educationmentioning

confidence: 99%

Teaching real‐time video processing theory by using an FPGA‐based educational system and the “learning‐by‐doing” method

Guzmán‐Ramírez

García

González

et al. 2017

Comp Applic In Engineering

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In the present study, we introduce a FPGA‐based educational system called RELI‐EVA (REconfigurable‐Logic‐based system for Implementation and Evaluation of real‐time Video processing and analysis of Algorithms), which has been integrated into a Computer and Electronic Engineering course by following the “learning‐by‐doing” approach. Therefore, the aim of this system is to provide engineering students with an intuitive tool in order to understand the main algorithms for real‐time video processing and create and test some new algorithms before their real implementation in physical systems. Moreover, with the aim of demonstrating the potential of the developed FPGA‐based system, the development of a practical example for edge detection is presented in order to support the theoretical basis of real‐time video processing. Additionally, a qualitative research method was followed to evaluate the proposed tool. A high percentage of the surveyed students corroborated the success of RELI‐EVA as part of an engineering course. © 2017 Wiley Periodicals, Inc. Comput Appl Eng Educ 25:376–391, 2017; View this article online at http://www.wileyonlinelibrary.com/journal/cae; DOI

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“…One core mainly affects the longitudinal edge of the image, and the other has a large impact on the horizontal edge of the image, and the maximum value is chosen as the output value between the two convolutions [12,13] . The result of the image operation is an image with a certain edge gray scale.…”

Section: Theoretical Analysis and Comparison Of Classical Edge Detecmentioning

confidence: 99%

Research on Edge Detection Algorithm in Digital Image Processing

Wu¹,

Liu²

2017

Proceedings of the 2017 2nd International Conference on Materials Science, Machinery and Energy Engineering (MSMEE 2017)

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Abstract.The image has many features, among which the edge is one of the most basic one. The purpose of edge detection is to obtain accurate edge positioning, which plays a vital role in computer vision and image analysis. Great detection of the image can also effectively suppress the generation of noise. There are many methods for edge detection in digital image processing. With the upgrading of science and technology, the recent emerging image edge detection algorithm becomes the organic synthesis of variety emerging image edge detection algorithms. Firstly, the theoretical analysis and LOG operator of the classical edge detection operator are studied emphatically. Then, the performance of the classical edge detection operator and the multi-scale algorithm of the digital image edge detection algorithm are fully explained. Finally, the digital image edge detection classification and digital image edge detection algorithm are described in detail.Edge detection method refers to a method of segmentation calculation on the edge of an image. The edge detection of the image is also a test of the basic characteristics of the image, and such information detection will carry a lot of image information. Therefore, the image edge detection algorithm plays an important role in the geometric analysis of the image and the application of the computer vision, and can provide a lot of reliable resources for the actual interpretation and data analysis of the image [1][2][3] . Digital image edge detection algorithm is based on image segmentation, image pixel recognition, partial image acquisition and other image analysis methods. When the image edge detection algorithm is used, it is necessary to perform the edge measurement and edge sampling of the image, so that the image can be understood and the image can be analyzed at the same time. Image edge detection algorithm has become one of the important research fields of image recognition and computer identification. Image edge detection algorithm also plays an important role in engineering application and engineering drawing. Image edge detection algorithm is one of the most basic analysis methods of image. In pursuit of simple algorithms, the image edge detection algorithm also deals with the balance between detection accuracy and noise immunity [4][5][6] . In this paper, the edge detection algorithm in digital image processing is studied deeply, and the conventional classical algorithm is studied. It is hoped that a kind of edge detection algorithm for digital image with simple calculation and balanced detection accuracy and anti-noise can be found. 1Theoretical Analysis and Comparison of Classical Edge Detection OperatorsImage edge refers to a collection which contains pixels grayscale with a certain level of change or a set of pixel changes around an image. There is a certain gradation gradient between the two different pixels. The edge feature of the image is one of the most important basic features of the image. Digital image edge can be divided into two categories: the firs...

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CoLFDImaP: A web‐based tool for teaching of FPGA‐based digital image processing in undergraduate courses

Cited by 17 publications

References 60 publications

Modeling, simulation, and implementation issues of CPGs for neuromorphic engineering applications

Modeling, simulation, and implementation issues of CPGs for neuromorphic engineering applications

Teaching real‐time video processing theory by using an FPGA‐based educational system and the “learning‐by‐doing” method

Research on Edge Detection Algorithm in Digital Image Processing

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