JNTUH B.Tech 4th Year 1 sem Information Technology R13 (4-1) Image Processing and Pattern Recognition (Elective – I) R13 syllabus.

JNTUH B.Tech 4th year (4-1) Image Processing and Pattern Recognition gives you detail information of Image Processing and Pattern Recognition (Elective – I) R13 syllabus It will be help full to understand you complete curriculum of the year.

Objectives

• Adequate background knowledge about image processing and pattern recognition
• Practical knowledge and skills about image processing and pattern recognition tools
• Necessary knowledge to design and implement a prototype of an image processing and pattern recognition application.

UNIT—I

Fundamental steps of image processing, components of an image processing of system. The image model and image acquisition, sampling and quantization, relationship between pixels, distance functions, scanner. Statistical and spatial operations, Intensity functions transformations, histogram processing, smoothing & sharpening — spatial filters Frequency domain filters, homomorphic filtering, image filtering & restoration, Inverse and weiner filtering, FIR weiner filter, Filtering using image transforms, smoothing splines and interpolation.

UNIT —II

Morphological and other area operations, basic morphological operations, opening and closing operations, dilation erosion, Hit or Miss transform, morphological algorithms, extension to grey scale images. Segmentation and Edge detection region operations, basic edge detection, second order detection, crack edge detection, gradient operators, compass and Laplace operators, edge linking and boundary detection, thresholding, region based segmentation, segmentation by morphological watersheds.

UNIT —III

Image compression: Types and requirements, statistical compression, spatial compression, contour coding, quantizing compression, image data compression-predictive technique, pixel coding, transfer coding theory, lossy and lossless predictive type coding, Digital Image Water marking.

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TEXT BOOKS

• Digital Image Processing Third edition, Pearson Education, Rafael C. Gonzalez, Richard E. Woods.
• Pattern recognition Principles: Julus T. Tou, and Rafel C. Gonzalez, Addision-Wesly Publishing Company.
• Digital Image Processing, M.Anji Reddy, Y.Hari Shankar, BS Publications.

REFERENCE BOOKS

• Image Processing, Analysis and Machine Vision, Second Edition, Milan Sonka, Vaclav Hlavac and Roger Boyle. Thomson learning
• Digital Image Processing — William k. Pratl —John Wiley edition.
• Fundamentals of digital image processing — by A.K. Jam, PHI.
• Pattern classification, Richard Duda, Hart and David strok John Wiley publishers.
• Digital Image Processing, S.Jayaraman,S. Esakkirajan, T.Veerakumar, TMH.
• Pattern Recognition, R.Shinghal, Oxford University Press.

Outcomes

• Ability to apply computer algorithms to practical problems.
• Ability to image segmentation, reconstruction and restoration.
• Ability to perform the classification of patterns.

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