The ongoing digitization of historical photographs in archives allows investigating the quality, quantity, and distribution these images. However, exact interior exterior camera orientations are usually lost during process. proposed method uses content-based image retrieval (CBIR) to filter images single buildings combination with metadata information. retrieved automatically processed an adapt...

In the medical field, content-based image retrieval (CBIR) is used to aid radiologists in the retrieval of images with similar contents. CBIR methods are usually developed for specific features of images, so that those methods are not readily applicable across different kinds of medical images. This study proposes a sound methodology for CBIR of mammograms, which is applicable to various format...

Benchmarking Content Based Image Retrieval (CBIR) systems allows researchers and developers to compare the strengths of different approaches, and is an essential step towards establishing the credibility of CBIR systems for commercial applications. Here we introduce the problem of developing a benchmark, discuss some of the issues involved, and provide a review of current and recent benchmarkin...

Digital media are rapidly replacing their analog counterparts. This development is accompanied by (i) the increasing amount of images present on the Internet, (ii) the availability of the Internet for an increasing number of people, (iii) a decline in digital storage costs, and (iv) the developments in personal digital video/photo cam-era's [1, 2, 3]. In anticipation of these developments, the ...

Even though it has extensively been shown that retrieval specific training of deep neural networks is beneficial for nearest neighbor image search quality, most these models are trained and tested in the domain landmarks images. However, some applications use images from various other domains therefore need a network with good generalization properties - general-purpose CBIR model. To best our ...

Multimedia data is growing rapidly in the current digital era, one of which image data. The increasing need for a large number datasets makes constraints faced eventually drain lot time and cause process description to be inconsistent. Therefore, method needed processing data, especially searching dataset find that are relevant query image. One proposed methods information based on content retr...

Most of the approaches of Content-Based Image Retrieval (CBIR) presume a linear relationship between different image features, and the efficiency of such systems was limited due to the difficulty in representing high-level concepts using low-level features. In this paper, a new architecture for a CBIR system is proposed; the Splines Neural Network-based Image Retrieval (SNNIR) system. SNNIR mak...

Developments in multimedia technology, increasing number of image retrieval functions and capabilities has led to the rapid growth of CBIR techniques. Colour histogram could be compared in terms of speed and efficiency. We have presented a modified approach based on a composite colour image histogram. A major research perspective in CBIR emphasize on matching similar objects based on shape, col...

Advances in data storage, data transmission, and image acquisition led to the creation of large image datasets. It became the motivation for systems that are able to efficiently retrieve images from these collections. This task has been addressed by the so-called Content-Based Image Retrieval (CBIR) systems. There are some quite powerful image descriptors designed to represent global features o...

Resumen. La recuperación de imágenes basada en su contenido propio (CBIR: Content–Based Image Retrieval), describe una serie de técnicas y métodos que utilizan contenidos visuales extráıdos de las propias imágenes a estudiar, para buscar o clasificar imágenes de acuerdo con los intereses de un usuario o sistema; ésta ha sido un área de investigación con notables progresos en la investigación te...