RA3701 Robotic Vision and Intelligence Syllabus:
RA3701 Robotic Vision and Intelligence Syllabus – Anna University Regulation 2021
COURSE OBJECTIVES:
1. To understand the basics concepts of optics and vision systems.
2. To learn and understand the fundamentals of image processing
3. To impart knowledge on object recognition and feature extraction.
4. To understand algorithms in image processing.
5. To demonstrate the various applications of machine vision system.
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
TOTAL: 45 PERIODS
COURSE OUTCOMES:
Upon Completion of the course, the students will be able to
CO 1: Know the various types of sensors, lightings, hardware and concept of machine vision.
CO 2: Acquire the image by the appropriate use of sensors, lightings and hardware.
CO 3: Apply the various techniques of image processing in real time applications.
CO 4: Select the suitable sensors, lightings and hardware.
CO 5: Apply the vision techniques in Robot vision system.
TEXT BOOKS:
1. Rafael C. Gonzales, Richard. E. Woods, “Digital Image Processing Publishers”, Fourth Edition
2. EmanueleTrucco, Alessandro Verri, “Introductory Techniques For 3D Computer Vision”, First Edition
REFERENCES
1. Yi Ma, Jana Kosecka, Stefano Soatto, Shankar Sastry, “An Invitation to 3-D Vision From Images to Models”, First Edition, 2004
2. Fu .K.S, Gonzalez .R.S, Lee .C.S.G, “Robotics – Control Sensing, Vision and Intelligence”, Tata McGraw-Hill Education, 2008.
3. RafelC.Gonzalez, Richard E.Woods,StevenL.Eddins, “Digital Image Processing using MATLAB”, 2nd edition, Tata McGraw Hill, 2010.