RA3701 deals with the semester VII B.E Robotics and Automation Syllabus at Anna University based on regulation 2021. In this article, we discuss the Robotic Vision and Intelligence Syllabus syllabus along with textbooks and references.
We intend to provide a full-planned syllabus for students to gain knowledge of the syllabus. It will give students to be equipped with perfect books and the required knowledge to prepare for the examinations. These are necessary to get a qualified certificate from the university with aggregate marks. Students must perform well to take a step forward toward their careers. They must earn a qualified degree help them to achieve success in their goals. In this article, RA3701 – Robotic Vision and Intelligence Syllabus will pioneer the way to do that. Hope the following information is useful. Don’t forget to share it with your classmates.
If you want to know more about the syllabus of B.E Robotics and Automation connected to an affiliated institution’s four-year undergraduate degree program. We provide you with a detailed Year-wise, semester-wise, and Subject-wise syllabus in the following link B.E Robotics and Automation Syllabus Anna University, Regulation 2021.
Aim Of Objectives:
- To understand the basics concepts of optics and vision systems.
- To learn and understand the fundamentals of image processing.
- To impart knowledge on object recognition and feature extraction.
- To understand algorithms in image processing.
- To demonstrate the various applications of machine vision system.
RA3701 – Robotic Vision and Intelligence Syllabus
Unit I: Image Acquisition
The Nature of Vision- Robot vision – Need, Applications – image acquisition – Physics of Light – Interactions of light – Refraction at a spherical surface – Thin Lens Equation – Illumination techniques – linear scan sensor, planar sensor, camera transfer characteristic, Raster scan, Image capture time, volume sensors, Image representation, picture coding techniques.
Unit II: Image Processing Fundamentals
Introduction to Digital Image Processing – Image sampling and quantization – Image enhancement: Gray Value Transformations, Radiometric Calibration, Image Smoothing – Geometric transformation – Image segmentation – Object Recognition and Image Understanding – Feature extraction: Region Features, Gray Value Features, Contour Features – Morphology – Edge extraction – Fitting and Template matching.
Unit III: Object Recognition And Feature Extraction
Image segmentation – Edge Linking – Boundary detection – Region growing-Region splitting and merging – Boundary Descriptors – Freeman chain code – Regional Descriptors – recognition structural methods – Recognition procedure, mahalanobic procedure.
Unit IV: Collison Fronts Algorithm
Introduction, skeleton of objects. Gradients, propagation, Definitions, propagation algorithm, Thinning Algorithm, Skeleton lengths of Top most objects.
Unit V: Robot Vision Application
Case study-Automated Navigation guidance by vision system – vision based de palletizing – line tracking – Automatic part Recognition. Image processing techniques implementation through Image Processing software.
Text Books:
- Rafael C. Gonzales, Richard. E. Woods, “Digital Image Processing Publishers”, Fourth Edition.
- EmanueleTrucco, Alessandro Verri, “Introductory Techniques For 3D Computer Vision”, First Edition.
References:
- Yi Ma, Jana Kosecka, Stefano Soatto, Shankar Sastry, “An Invitation to 3-D Vision From mages to Models”, First Edition, 2004.
- Fu . K.S, Gonzalez .R.S, Lee . C.S.G, “Robotics – Control Sensing, Vision and Intelligence”, Tata McGraw-Hill Education, 2008.
- RafelC.Gonzalez, Richard E. Woods, Steven L.Eddins, “Digital Image Processing using MATLAB”, 2nd edition, Tata McGraw Hill, 2010.
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