A Beginner’s Guide to Image Preprocessing Techniques
Intelligent Signal Processing and Data Analysis Series

For optimal computer vision outcomes, attention to image pre-processing is required so that one can improve image features by eliminating unwanted falsification. This book emphasizes various image pre-processing methods which are necessary for early extraction of features from the image. Effective use of image pre-processing can offer advantages and resolve complications that finally results in improved detection of local and global features. Different approaches for image enrichments and improvements are conferred in this book that will affect the feature analysis depending on how the procedures are employed.

Key Features

• Describes the methods used to prepare images for further analysis which includes noise removal, enhancement, segmentation, local, and global feature description





• Includes image data pre-processing for neural networks and deep learning





• Covers geometric, pixel brightness, filtering, mathematical morphology transformation, and segmentation pre-processing techniques





• Illustrates a combination of basic and advanced pre-processing techniques essential to computer vision pipeline





• Details complications to resolve using image pre-processing

1. Perspective of Image Preprocessing on Image Processing. 2. Pixel Brightness Transformation Techniques. 3. Geometric Transformation Techniques. 4. Filtering Techniques. 5. Segmentation Techniques. 6. Mathematical Morphology Techniques. 7. Other Applications of Image Preprocessing.

Jyotismita Chaki, PhD. has done her PhD (Engg) from Jadavpur University, School of Education Technology Department, Kolkata, India. Her research interests include: Computer Vision and Image Processing, Pattern Recognition, Medical Imaging, Soft computing, Data mining, Machine learning. She has published 14 international conferences and journal papers. She has also served as a Program Committee member of 2nd International Conference on Advanced Computing and Intelligent Engineering 2017 (ICACIE-2017), 4TH International Conference on Image Information Processing (ICIIP-2017).

Nilanjan Dey, PhD. is currently associated with Department of Information Technology, TechnoIndia College of Technology, Kolkata, W.B., India. He holds an honorary position of Visiting Scientistat Global Biomedical Technologies Inc., CA, USA and Research Scientist of Laboratory of AppliedMathematical Modeling in Human Physiology, Territorial Organization of- Scientific and EngineeringUnions, BULGARIA. He is an Associate Researcher of Laboratoire RIADI, University of Manouba, TUNISIA. He is the Associated Member of Wearable Computing Research lab, University of Reading,London, UK.

His research topic is Medical Imaging, Soft computing, Data mining, Machine learning, Rough sets,Computer Aided Diagnosis, Atherosclerosis. He has 25 books and 300 international conferences andjournal papers. He is the Editor-in-Chief of International Journal of Ambient Computing andIntelligence (IGI Global), US (Scopus, ESCI, ACM dl and DBLP listed), International Journal of RoughSets and Data Analysis (IGI Global), US. Co-Editor-in-chief of International Journal of SyntheticEmotions (IJSE), IGI Global, US, and International Journal of Natural Computing Research (IGI Global), US. Series Editor of Advances in Geospatial Technologies (AGT) Book Series, (IGI Global), US, SeriesEditor of Advances in Ubiquitous Sensing Applications for Healthcare (AUSAH), Elsevier. Executive Edi