CBIR using content frequency and colour features
نویسندگان
چکیده
منابع مشابه
Content-based image retrieval using colour and shape features
Content-Based Image Retrieval (CBIR) uses the visual contents of an image such as color, shape, texture, and spatial layout to represent and index the image. Active research in CBIR is geared towards the development of methodologies for analyzing, interpreting cataloging and indexing image databases. In addition to their development, efforts are also being made to evaluate the performance of im...
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A perceptual approach to generating features for use in indexing and retrieving images is described. Salient regions that immediately attract the eye are colour (textured) regions that usually dominate an image. Features derived from these will allow search for images that are similar perceptually. We compute colour features and Gabor colour texture features on regions identified from a coarse ...
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Digital photography faces the challenges of image storage, retrieval and provenance at the consumer and commercial level. One major obstacle is in the computational cost of image processing. Solutions range from using high-throughput computing systems to automatic image annotation. Consumers can not dedicate computing systems to image processing and handling nor do consumers have large-scale im...
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Content-Based Image Retrieval (CBIR) is a challenging task which retrieves the similar images from the large database. Most of the CBIR system uses the low-level features such as colour, texture and shape to extract the features from the images. In Recent years the Interest points are used to extract the most similar images with different view point and different transformations. In this paper ...
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ژورنال
عنوان ژورنال: International Journal of Image Mining
سال: 2021
ISSN: 2055-6039,2055-6047
DOI: 10.1504/ijim.2021.10038786