
Design and analysis of an efficient image retrieval technique
LAP Lambert Academic Publishing
Published on 18. May 2021
Book
Paperback/Softback
92 pages
978-620-3-86193-8 (ISBN)
Description
Content-based image retrieval uses features at a low or pixel image level for such color, texture and shape. And on the basis of this feature get the right photos from storage media. But here the key problem for the researcher is to find the most relevant image from the database first or for a small amount of search iteration. In the short term the HSV color histogram is an excellent feature of the image and has been used in various investigative programs. In this article, the HSV Color histogram is based on an image to extract a color element and measure the value of the histogram by 72 different barrels. The stitching element is removed using a discrete wavelet transform that helps to remove the intricate pattern pattern present in the image. The definition of a histogram feature is used to determine the location and geometric details of an image by subtracting the edges present in the image and combining these elements into a single element vector so that it can properly enlarge the image. In the process of classifying the vector classifier machine is used to classify images into different categories accordingly.
More details
Language
English
Dimensions
Height: 220 mm
Width: 150 mm
Thickness: 7 mm
Weight
155 gr
ISBN-13
978-620-3-86193-8 (9786203861938)
Schweitzer Classification
Persons
Mohd. Aquib Ansari has completed his B.E. from SATI Vidisha in Information Technology (2014). He has done his M.Tech. from MITS Gwalior in Information Technology (2017). He is currently pursuing his Ph.D. from MNNIT Allahabad. His research interest includes Digital Image Processing, Computer Vision, Artificial Intelligence and Network Security.