Feature Based Comparison of Text Based Image Retrieval and Context Based Image Retrieval ImagesAuthor : Gagandeep Kaur, Deepam Goyal and Rajeev Kumar Dang
Volume 7 No.2 Special Issue:November 2018 pp 6-11
Image processing is a field to process the images according to horizontal and vertical axis to form some useful results. It deals with edge detection, image compression, noise removal, image segmentation, image identification, image retrieval and image variation etc. Customarily, there are two techniques i.e. text based image retrieval and content based image retrieval that are used for retrieving the image according to features and providing color to all pixel pairs. The system retrieval that is based on TBIR assists to recover an image from the database using annotations. CBIR extorts images to form a hefty degree database using the visual contents of an original image that is called low level features or features of an image. These visual features are extracted using feature extraction and then match with the input image. Histogram, color moment, color correlogram, Gabor filter and wavelet transform are various CBIR techniques that can be used autonomously or pooled to acquire enhanced consequences. This paper states about a novel technique for fetching the images from the image database using two low level features namely color based feature and texture based features. Two techniques- one is color correlogram (for color indexing) and another is wavelet transform (for texture processing) has also been introduced.
Context based image retrieval (CBIR), Feature extraction; Text based image retrieval (TBIR)
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