NDLI: Shape Extraction Using Edge Detection Techniques

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Shape Extraction Using Edge Detection Techniques

Content Provider	ACM Digital Library
Author	Gohel, Jyoti Patel, Maulika S. Joshi, Divya Ami, Nagma
Abstract	Content Based Image Retrieval (CBIR) is a system that searches for similar images from a large image database according to users' specification. Digital image database is growing rapidly in size as a result of technological advancements. Traditional systems like text based image retrieval faces too many problems like human perception, deeper needs, image annotation and etc. Thus it is difficult to support a variety of task-dependent queries for traditional systems. CBIR systems comprehend a wide areas, viz. image segmentation, image feature extraction, representation, feature matching, storage and indexing, image retrieval - making CBIR system development a challenging task. The visual content of an image is analyzed features (i.e., color, shape, texture) extracted from the image. CBIR system is used in Medical Imagery Retrieval, Finger Print Retrieval, Satellite Imagery Retrieval, Internet, and Photo Collections. The paper focuses upon shape based image retrieval. With the help of three different edge detection algorithms, they extract the shape features from a given input image.
Starting Page	1
Ending Page	5
Page Count	5
File Format	PDF
ISBN	9781450332163
DOI	10.1145/2677855.2677927
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2014-11-14
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Shape feature Sobel operator Edge detection algorithms Canny edge detection Prewitt operator
Content Type	Text
Resource Type	Article

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