Both soft computing techniques and machine learning algorithms have very important tasks in image processing applications. With the artificial intelligence (AI)-based applications emerging in the market today, image processing techniques have gained more attention. This rich collection covers various modern image processing applications.

The book has four parts and 32 well-written chapters. Part 1, “Image Segmentation,” has six chapters. Soft computing techniques, namely whale optimization, swarm optimization, and evolutionary optimization, are applied for image segmentation. Color spaces, color clustering, and representation for image segmentation are also presented. I liked the chapter on swarm optimization for liver image segmentation. It neatly provides overviews of various swarm optimization techniques, namely grey wolf optimization, the artificial bee colony (ABC) algorithm, and antlion optimization, and proposes three swarm optimization-based techniques for liver image segmentation. Experimental results along with performance analyses of the three proposed algorithms are presented.

Part 2 is on image processing applications in medicine. Its six chapters cover various applications, namely liver tumor recognition, lymphoblastic leukemia diagnosis, breast cancer detection, assessment of coronary disease, and glaucoma monitoring. Support vector machines (SVMs), principal component analysis (PCA), texture analysis, singular value decomposition (SVD), wavelet transforms, and fuzzy c-means methods are applied for the medical image processing applications.

Part 3 (nine chapters) covers security and biometric applications, from personal identification, video surveillance, and smart homes to Aadhar-based smart card systems. Multimodal biometrics such as fingerprint, iris, face, gait, deoxyribonucleic acid (DNA), and palate are employed to develop authenticity. Watermarking, steganography, and cryptography-based security applications using image processing techniques are also discussed.

The fourth part, “Object Analysis and Recognition in Digital Images,” consists of 11 well-written chapters. It covers many modern applications, including age synthesis, peer-to-peer (P2P) video delivery systems, image projection analysis, lip protrusion estimation, and robotic grasping. This part explores the latest object recognition applications using soft computing techniques.

Every chapter is well written and comprehensive. New algorithms are presented with experimental results and performance comparisons. The reference materials used are clearly cited.

Overall, this well-edited volume consists of rich, highly useful, and relevant material. It will be useful for research students working in soft computing, machine vision, and image processing fields.