SIPTool: The \u27Signal and Image Processing Tool\u27 An Engaging Learning Environment (original) (raw)
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SIPTool: the 'Signal and Image Processing Tool'-an engaging learning environment
31st Annual Frontiers in Education Conference. Impact on Engineering and Science Education. Conference Proceedings (Cat. No.01CH37193)
With the SIPTool, students create an integrated system that includes their processing routine along with image/signal acquisition and display. This integrated system is a very different result than the 'haphazard' line-by-line processing steps that students may or may not successfully stumble through in a MatLab environment, as they follow a given example. The SIPTool-based implementation is much more like a complete, commercial product.
DataLab-J: A signal and image processing laboratory for teaching and research
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Abstract DataLab-J is a software signal and image processing laboratory which has proved effective both as an educational" workbench" and in practical operational use. It requires a pedagogical tool, a research environment, and a fully operational data analysis system, ie, it is used not only in undergraduate engineering courses, but in graduate study and general research.
A software system for laboratory experiments in image processing
IEEE Transactions on Education, 2000
Laboratory experiments for image processing courses are usually software implementations of processing algorithms, but students of image processing come from diverse backgrounds with widely differing software experience. To avoid learning overhead, the software system should be easy to learn and use, even for those with no exposure to mathematical programming languages or object-oriented programming. The class library for image processing (CLIP) supports users with knowledge of C, by providing three C++ types with small public interfaces, including natural and efficient operator overloading. CLIP programs are compact and fast. Experience in using the system in undergraduate and graduate teaching indicates that it supports subject matter learning with little distraction from language/system learning.
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Due to the increasing number of applications of digital image processing in the last years, we have included a course on tlus topic in the list of courses offered by the Electrical Engineering Department. This course has been taught at graduate level, however, undergraduate students at senior level are allowed to take it as an optional course. An educational software package has been developed to be used as a complement of the theory revised in the lectures. This package was implemented in Visual Basic*, which is a visual programming language to create applications in a Windows* environment. The image to be processed can be generated using the editor included, or can be imported using images in a bmp format. The images consist of a 64x64 pixels array with 16 gray levels. This size was considered enough to perform, with educational purpose, most of the operations in the spatial and frequency domains in a reasonable amount of time. Operations available include manipulation in the space and frequency domains, such as 2-D convolution, gray level transformations: linear filtering, histogram equalization, morphological filtering, and others. Examples show how the package can be useful as a lecture aid and as a lab assistance tool. The image to be processed can be generated using the editor included, or can be imported using images in a bmp format. A graphical interface allows the user to activate available operations through a menu selection.
The SIVA demonstration gallery for signal, image, and video processing education
IEEE Transactions on Education, 2002
The techniques of digital signal processing (DSP) and digital image processing (DIP) have found a myriad of applications in diverse fields of scientific, commercial, and technical endeavor. DSP and DIP education needs to cater to a wide spectrum of people from different educational backgrounds. This paper describes tools and techniques that facilitate a gentle introduction to fascinating concepts in signal and image processing. Novel LabVIEW-and MATLAB-based demonstrations are presented, which, when supplemented with Web-based class lectures, help to illustrate the power and beauty of signal and image-processing algorithms. Equipped with informative visualizations and a user-friendly interface, these modules are currently being used effectively in a classroom environment for teaching DSP and DIP at the University of Texas at Austin (UT-Austin). Most demonstrations use audio and image signals to give students a flavor of real-world applications of signal and image processing. This paper is also intended to provide a library of more than 50 visualization modules that accentuate the intuitive aspects of DSP algorithms as a free didactic tool to the broad signal and image-processing community.
Introductory computational science using MATLAB and image processing
Procedia Computer Science, 2010
We describe a new course designed to introduce engineering students to computational thinking. One of the most significant challenges in teaching an introductory-level applied computing course is that students are not expected to have substantial math and science experience. To address this, we have developed exercises which use edge detection and basic image processing to motivate the use of programming MATLAB in a non-trivial scientific application. MATLAB is a popular high-level programming language and environment which supports a wide range of computational science applications. MATLAB has strong support for operating on image data, which allows us to balance solving practical engineering problems with basic core concepts of computer science such as functional abstraction, conditional execution, and iteration.
Digital Signal Processing/Image Processing: Freshman To Senior Year
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A hands-on project course, which focuses on Digital Signal Processing (DSP) hardware and applications through the use of standard kits, is introduced at the senior level. Since these DSP kits are important and relatively easy to interface, they can be used to introduce first year students to the design and application process of digital Signal/Image processing despite their lack of theoretical background in this subject. This paper discusses one of the experiments conducted by a group of freshman students, and shows that it is not too early to introduce some practical advanced topics to freshmen.
A Windows-Based Interface for Teaching Image Processing
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The use of image processing in research represents a challenge to the scientific community interested in its various applications but is not familiar with this area of expertise. In academia as well as in industry, fundamental concepts such as image transformations, filtering, noise removal, morphology, convolution/deconvolution among others require extra efforts to be understood. Additionally, algorithms for image reading and visualization in computers are not always easy to develop by inexperienced researchers. This type of environment has lead to an adverse situation where most students and researchers develop their own image processing code for operations which are already standards in image processing, a redundant process which only exacerbates the situation. The research proposed in this article, with the aim to resolve this dilemma, is to propose a user-friendly computer interface that has a dual objective which is to free students and researchers from the learning time needed for understanding/applying diverse imaging techniques but to also provide them with the option to enhance or reprogram such algorithms with direct access to the software code. The interface was thus developed with the intention to assist in understanding and performing common image processing operations through simple commands that can be performed mostly by mouse clicks. The visualization of pseudo code after each command execution makes the interface attractive, while saving time and facilitating to users the learning of such practical concepts. ß
Digital images are ubiquitous in today's world, and the number of images available on the internet is exploding. Images are an important form of data in many fields. Examples include microscopy in biology, MRI and CT in medicine, satellite imagery in geology and agriculture, fingerprint and face images in security and many others. Digital image processing field deals with manipulation of images through computers, which takes images as inputs, applies an efficient algorithm and produces images as output. This course introduces to the students the fundamentals of digital image processing, covering topics from the following list: image models, image representation, various operations, transforms, techniques for enhancement, restoration, segmentation, morphological operations, compression and image analysis.