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Content-Based Image Retrieval (CBIR) is a scaffold that can prevail over the above revealed crisis as it is based on the visual analysis of contents that are part of the query image. In this book, the features like shape, texture, edge, HSV colour are extracted after applying phone shading in order to flatter out the dull surface of the image, feature extracted values are used to find the similarity between input query image and the db image. It can be measured using Euclidean and quadratic distance formula. The image is ranked according to the minimum distance value. The advantage of CBIR…mehr

Produktbeschreibung
Content-Based Image Retrieval (CBIR) is a scaffold that can prevail over the above revealed crisis as it is based on the visual analysis of contents that are part of the query image. In this book, the features like shape, texture, edge, HSV colour are extracted after applying phone shading in order to flatter out the dull surface of the image, feature extracted values are used to find the similarity between input query image and the db image. It can be measured using Euclidean and quadratic distance formula. The image is ranked according to the minimum distance value. The advantage of CBIR over TBIR (Text-Based Image Retrieval) are among other image retrieval methods, CBIRl is an approach that exclusively relies on the visual features, such as color histogram, texture, shape, and so forth, of the images. One of the obvious advantages of CBIR over other method is that It can be done in a fully automatic process since the visual features are automatically extracted.
Autorenporträt
Dr. D. Magdalene Delighta Angeline is Assistant Professor in the Department of Computer Science and Engineering in Joginpally B.R. Engineering College, Hyderabad, India. She obtained her Ph.D in Computer Science from Bharathiar University. She has over 12 years of Teaching Experience and published more International journal papers and books.