Feature Extraction using Overlap Blocks for Content based Image Retrieval
نویسندگان
چکیده
منابع مشابه
Feature Selection and Extraction for Content-Based Image Retrieval
Content-Based Image Retrieval is a technique that utilizes the visual content of an image to search for similar images in large scale image databases. The visual content of an image represents the low-level features extracted from the image. These primarily constitute color, shape and texture features. The precision of image classification and image retrieval is mainly based on image feature ex...
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Content based image retrieval (CBIR) is a challenging problem due to large size of the image database, difficulty in recognizing images, difficulty in devising a query and evaluating results in terms of semantic gap, computational load to manage large data files and overall retrieval time. Feature extraction is initial and important step in the design of content based image retrieval system. Fe...
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Content based image retrieval (CBIR) is an effective method of retrieving images from large image resources. CBIR is a technique in which images are indexed by extracting their low level features like, color, texture, shape, and spatial location, etc. Effective and efficient feature extraction mechanisms are required to improve existing CBIR performance. This paper presents a novel approach of ...
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The emergence of multimedia technology and the rapidly expanding image collections on the Internet have attracted significant research efforts in providing tools for effective retrieval and management of visual data. The need to find a desired image from a large collection is shared by many professional groups, including journalists, design engineers and art historians. Difficulties faced by te...
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ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2011
ISSN: 0975-8887
DOI: 10.5120/3401-4738