Image Retrieval by using histogram equalization and DBTCF using SVM
| Author(s) | : | Ayushi Godiya, L.D Mahor |
| Institution | : | Dept. of CSE/IT, NITM College,Gwalior, India |
| Published In | : | Vol. 4, Issue 11 — November 2017 |
| Page No. | : | 52-59 |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
Retrieving images as of from vast quantity of database which is based on to their content are beingrecognized content based image retrieval. Efficiency of any CBIR system is depend on features mined to stand for animage. As a outcome feature extraction is crucial step in design and the development of some CBIR. Most normally usedfeatures to signify images are Color, texture and shape. Here the Block truncation coding feature known as (BTCF) isused so as to compress the image. Further it give thought of Support Vector Machine also known (SVM) classifier. Inpaper the block of data is also divided into different chunks, so that image of single instance can be stored in thesechunks. So replication will be enhanced with the aid of compression techniques which is discussed in detail. Here basicCBIR system is being developed by the combine features like color correlogram , color moments and Gabor wavelettransform all along by way of histogram descriptor. Further outcome is being obtained are then compared throughCBIR system is using the SVM classifier
Ayushi Godiya, L.D Mahor, “Image Retrieval by using histogram equalization and DBTCF using SVM”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 4, Issue 11, pp. 52-59, November 2017.
