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Image Retrieval is a technique of searching, browsing, and retrieving the images from an image database. There are two types of different image retrieval techniques namely text based image retrieval and content based image retrieval techniques. Text-Based image retrieval uses traditional database techniques to manage images. Content-based image retrieval (CBIR) uses the visual features of an image...
Content based image retrieval (CBIR) refers to the ability to retrieve images on the basis of image content. In our work, we describe an approach to CBIR for various database images that relies on human input machine learning and computer vision. More specifically we apply expert level human interaction for solving that aspect of the problem and we employ machine learning algorithms to allow the system...
This paper presents a new approach to content-based image retrieval by using dynamic indexing and guided search in a hierarchical structure, and extending data mining and data warehousing techniques. The proposed algorithms include: a wavelet-based scheme for multiple image feature extraction, the extension of a conventional data warehouse and an image database to an image data warehouse for dynamic...
Content-based image retrieval (CBIR) techniques are becoming increasingly important in various fields. One of the most important steps in CBIR systems is feature extraction. However, using not appropriate features in heterogeneous image database during retrieval process does not provide a complete description of an image. Indeed, each feature is able to describe some characteristics related to the...
In this paper, we propose to use K-means clustering for the classification of feature set obtained from the histogram refinement method. Histogram refinement provides a set of features for proposed for Content Based Image Retrieval (CBIR). Standard histograms, because of their efficiency and insensitivity to small changes, are widely used for content based image retrieval. But the main disadvantage...
This paper presents an auto-annotation system with simple pre-processed segmentation for digital color image. Recently, annotation techniques become one popular method for image retrieval system in image database management, image recognition system and so on. In the paper, we propose a two-step approach for image annotation. Firstly, the color image is needed to be segmented into two parts: the main...
In this paper, an automatic human face detection approach using colour analysis is applied for content-based image annotation. In the face detection, the probable face region is detected by adaptive boosting algorithm, and then combined with a colour filtering classifier to enhance the accuracy in face detection. The initial experimental benchmark shows the proposed scheme can be efficiently applied...
Currently, most content based image retrieval (CBIR) systems operate on all images, without sorting images into different types or categories. Different images have different characteristics, and thus often require different analysis techniques and query types. Additionally, placing an image into a category can help the user to navigate retrieval results more effectively. To categorise an image, firstly...
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