This book introduces a range of image color feature extraction techniques. Readers are encouraged to try implementing the techniques discussed here on their own, all of which are presented in a very simple and step-by-step manner. In addition, the book can be used as an introduction to image color feature techniques for those who are new to the research field and software. The techniques are very easy to understand as most of them are described with pictorial examples. Not only the techniques themselves, but also their applications are covered. Accordingly, the book offers a valuable guide to these tools, which are a vital component of content-based image retrieval (CBIR).

Introduces a range of image color feature extraction techniques Presents all techniques step-by-step with pictorial examples Discusses applications of different image color feature extraction techniques

Autorentext
Dr. Jyotismita Chaki is an Associate Professor at the School of Computer Science and Engineering, Vellore Institute of Technology, India. She holds a Ph.D. in Engineering from Jadavpur University, Kolkata, and her research interests encompass Computer Vision, Image Processing, Pattern Recognition, Medical Imaging, Artificial Intelligence, and Machine Learning. Dr. Chaki is an author and editor, with a substantial body of work including five authored books published by renowned presses like Springer and CRC Press, and six edited books published by CRC Press and Elsevier. She has also published many research articles in high-impact, SCIE-indexed journals, the majority of which are ranked in the top quartiles (Q1 and Q2). In recognition of her contributions, Dr. Chaki was named the world's top 2% scientist by Stanford University and Elsevier in 2024. She is also a Senior Member of the IEEE. Dr. Chaki's editorial contributions are extensive, currently serving as editor for 9 journals, including Engineering Applications of Artificial Intelligence (Elsevier), Scientific Reports (Nature Portfolio), Discover Applied Sciences (Springer Nature), PLOS ONE, PeerJ Computer Science, Computer and Electrical Engineering (Elsevier), Array (Elsevier), Machine Learning with Applications (Elsevier), and BMC Artificial Intelligence.

Inhalt

Introduction to Image Color Feature.- Histogram based Image Color Feature.- : MPEG-7 based Image Color Feature.- Other Image Color Feature Extraction Techniques.- Applications of Color Features.