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operations beyond trivial low-level processes and region-based frameworks. Also, it manipulates a rich query language, consisting of both Boolean and quantification operators, which therefore leads to optimized user interaction and increased retrieval performance. Experimental results on a test collection of 2500 color personal
natural language use. Even though word sense and concept extraction is major challenge which comes up with keywords. Information can be presented in better way with image presentation, which is been used in news portals to communicate fastly happing news and social websites instagram Facebook, flicker .user purchase goods by
This paper proposes the use of content base image retrieval (CBIR) techniques for indexing and retrieval of handwritten documents in Thai language. Issues associated with Thai handwritten documents are the lack of spacing between words, multi-level alphabets and different writing styles. This causes low recognition
keywords. One set consists of colors-keywords and the other set consists of words. Experiments were performed to demonstrate the effectiveness of the proposed technique.
regions and words. The third and fourth approaches are based on segmenting the images into homogeneous regions. Both of these approaches rely on a clustering algorithm to learn the association between visual features and keywords. The clustering task is not trivial as it involves clustering a very high-dimensional and sparse
using feature vector. We do static analysis over computed features to get distinguishing feature descriptors. Maximum similarity i.e. minimum distance allows us to find the query relevant combined pictures and associated relevant words. For textual part of the query we compute the concepts (keywords as well as synonyms of
have resolved most difficulties when a user is able to provide appropriate keywords of his/her search target. Nevertheless, some important events which are etched deeply in one's memory may not be clearly defined as a few keywords or even easily recalled. Thus, we propose in this work to provide some visual suggestions to
A picture is worth a thousand words. Yes, but which ones? Content-based image retrieval (CBIR) is the application of computer vision to the image retrieval problem. The image retrieval problem is the problem of searching for digital images in large databases. ldquoContent-basedrdquo means that the search will analyze
retrieval system from plural key images using the self-organizing map with refractoriness makes use of this property in order to retrieve plural similar images. In this image retrieval system, as the image feature, not only color information but also spectrum, impression words and keywords are employed. In the proposed system
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.