What is Content Based Image Retrieval Content-based image retrieval, also known as query by image content and content-based visual information retrieval (CBVIR), is the application of computer vision techniques to the problem of image retrieval, which is the difficulty of searching for digital images in big databases. Other names for this technique include content-based visual information retriev. In contrast to the conventional concept-based methods, content-based picture retrieval is a more recent development. How you will benefit (I) Insights, and validations about the following topics: Chapter 1: Content-based image retrieval Chapter 2: Information retrieval Chapter 3: Image retrieval Chapter 4: Automatic image annotation Chapter 5: Tag cloud Chapter 6: Video search engine Chapter 7: Image organizer Chapter 8: Image meta search Chapter 9: Reverse image search Chapter 10: Visual search engine (II) Answering the public top questions about content based image retrieval. (III) Real world examples for the usage of content based image retrieval in many fields. Who this book is for Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Content Based Image Retrieval.

What is Reverse Image Search Reverse image search is a content-based image retrieval (CBIR) query technique that involves providing the CBIR system with a sample image that it will then base its search upon; in terms of information retrieval, the sample image is very useful. In particular, reverse image search is characterized by a lack of search terms. This effectively removes the need for a user to guess at keywords or terms that may or may not return a correct result. Reverse image search also allows users to discover content that is related to a specific sample image or the popularity of an image, and to discover manipulated versions and derivative works. How you will benefit (I) Insights, and validations about the following topics: Chapter 1: Reverse image search Chapter 2: Web crawler Chapter 3: Image retrieval Chapter 4: Recommender system Chapter 5: Document retrieval Chapter 6: Content-based image retrieval Chapter 7: Automatic image annotation Chapter 8: Inverted index Chapter 9: Google Images Chapter 10: Social search (II) Answering the public top questions about reverse image search. (III) Real world examples for the usage of reverse image search in many fields. Who this book is for Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Reverse Image Search.