International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 10 Issue: 06 | Jun 2023
p-ISSN: 2395-0072
www.irjet.net
Implementation of Computer Vision Applications usingOpenCV in C++ Adwait Bhave, Vaishnavi Jadhav, Punit Bhandari, Vaishnavi Patil Department of Electronics and Telecommunication Engineering, Pune Vidyarthi Griha’s College of Engineering Technology Project Guide: Prof. Anand Najan Sponsored by NSM Solutions Pvt. Ltd.Industry guide: Mr. Nishad Mande -----------------------------------------------------------------------***----------------------------------------------------------------------
Abstract — Computer Vision (CV) has emerged as a critical field in various domains, ranging from autonomous vehicles to medical imaging. OpenCV, an open-source computer vision library, provides a rich set of functions and algorithms for image processing, feature detection, object recognition, and more. This paper presents a comprehensive study of integrating OpenCV with C++, aiming to explore its potential for developing robust and efficient CV applications. We present practical examples that demonstrate the seamless integration of OpenCV with C++. We showcase real-world applications such as facial recognition, motion detection, and augmented reality, highlighting the versatility and extensibility of the OpenCV library when utilized alongside the C++ programming language
Computer vision systems can recognise and categorise objects in pictures or video streams by extracting features, matching patterns, and using machine learning methods. Image processing enables applications like object tracking, surveillance, and autonomous navigation by helping to distinguish things based on colour, shape, texture, or other visual properties. Tools for picture analysis and interpretation are provided by image processing in order to get useful data from images. This involves activities like measuring, motion analysis, scene comprehension, and Object and Text Recognition, for the following given usecases
Keywords – Computer Vision, OpenCV, C++, Text Recognition, colour detection, barcode decoding, Text on Image I.
INTRODUCTION
1.
Colour Detection
2.
Barcode Decoding
3.
Text Recognition
4.
Text on Image
II.
OpenCV (Open-Source Computer Vision Library) is a widely-used open-source computer vision and machine learning software library. It provides developers with a rich set of tools and algorithms for image and video processing, object detection and recognition, and other computer vision tasks. OpenCV is written in C++, which makes it a powerful and efficient library for real-time computer vision applications. C++ provides a powerful and flexible environment for implementing CV algorithms, leveraging features like operator overloading, templates, and memory management. We explore how C++ enhances the performance of OpenCVbased applications through its low-level control and efficient resource utilization. We will be using various OpenCV and image processing functions and algorithms like Grey-scaling, edge-detection, morphology, contours, thresholding etc.
LITERATURE REVIEW
The field of computer vision in C++ is active and quickly developing, with many new scientific discoveries and useful applications. In our Project we used four different use cases of computer-vision which we implemented using the programming language C++. There are large number of studies and research in the field of computer-vision but it is all done in the programming language of python. Implementing it in C++ was a challenge in itself as not many researches were there regarding our use cases. Here is a summary of the important studies. 1.
"Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library" by Adrian Kaehler and Gary Bradski - This book is a comprehensive guide to the OpenCV library and is ideal for beginners who want to learn computer vision using C++ and OpenCV.
Computer vision tasks such as object detection and recognition benefit from image processing techniques.
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