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پیدا کردن جواب نظرسنجی با پردازش تصویر
در این پروژه جواب برگه های نظرسنجی اسکن شده با پردازش تصویر استخراج می شود.
برگه نظرسنجی نمونه که شامل دو سوال چهار گزینه ای است پیوست شده است.
برنامه با پسوند txt پیوست شده است.
LOW DIMENSIONAL MANIFOLD MODEL FOR IMAGE PROCESSING
∗ STANLEY OSHER † , ZUOQIANG SHI ‡ , AND WEI ZHU §
2.
First Order Algorithms in Variational Image Processing
Introduction: Variational methods in imaging are nowadays developing towards a quite universal and flexible tool, allowing for highly successful approaches on tasks like denoising, deblurring, inpainting, segmentation, super-resolution, disparity, and optical flow estimation. The overall structure of such approaches is of the form
3.
Parametrized system level design: Real-time XRay image processing case study Conference Paper ·
July 2016 DOI: 10.1109/ASAP.2016.7760793
Abstract—Complex embedded systems are used to facilitate real-time data processing applications. To cope with their surroundings, these systems need to provide some form of parameterization. Developing such systems is challenging as the system needs to execute in a stable and consistent way with the parameterization. In this paper, we want to present how we can develop such a system from C-code using the Compaan technology and show a real-time medical X-Ray image processing case study. Our purpose is to evaluate the system level synthesis flow of Compaan and to assess if the Compaan technology is capable of realizing such complex parametrized system.
4.
Machine Learning for Plant Phenotyping Needs Image Processing
Keywords: image processing, machine learning, plant phenotyping, stress
We found the article by Singh et al. [1] extremely interesting since it introduces and showcases the utility of machine learning for high throughput data-driven plant phenotyping. With this letter we want to emphasize the role that image analysis and processing have in the phenotyping pipeline beyond what [1] suggests, both in analyzing phenotyping data (e.g., to measure growth) but also when providing effective feature extraction to be used by machine learning. Key recent reviews have shown that it is image analysis itself (what the authors of [1] consider as part of pre-processing) that has brought a renaissance in phenotyping [2]. At the same time, the lack of robust methods to analyze these images is now the new bottleneck [3-5]. And this bottleneck is not easy to overcome. As the following aims to illustrate, it is coupled to the imaging system and the environment but also to the analysis task at hand and requires new skills to help deal with the challenges introduced.
5.Volume 3, Issue 3, March-2016, pp. 119-122 ISSN (O): 2349-7084
Review of Various Image Processing Techniques for Currency Note Authentication
Trisha Chakraborty, Nikita Nalawade, Abhishri Manjre, Akanksha Sarawgi, Pranali P Chaudhari Abstract:- In cash transactions, the biggest challenge faced is counterfeit notes. This problem is only expanding due to the technology available and many fraud cases have been uncovered. Manual detection of counterfeit notes is time consuming and inefficient and hence the need of automated counterfeit detection has raised. To tackle this problem, we studied existing systems using Matlab, which used different methods to detect fake notes
. Keywords – Counterfeit, Image Processing, Matlab, Cloud, Map Reduce
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فهرست
تحقیق و بررسی کاربرد های پردازش تصویر
مقدمه ای بر پردازش تصویر
کاربردهای بازشناسی الگو در پردازش تصویر
بازشناسی نوری حروف (OCR)
تصویر محیط برنامه
این فایل که شامل 28 اسلاید است به بررسی مفاهیم اصلی پردازش تصویر، الگوهای رنگ و ارتقاتصویر بحث می کند. و کاربردهای اصلی پردازش تصویر را بیان میکند.