| contributor author | Thilagamani, S. | |
| contributor author | Shanthi, N. | |
| date accessioned | 2017-05-09T01:06:05Z | |
| date available | 2017-05-09T01:06:05Z | |
| date issued | 2014 | |
| identifier issn | 1530-9827 | |
| identifier other | jcise_014_02_021006.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/154225 | |
| description abstract | The problem of segmenting the object from the background is addressed in the proposed Gaussian and Gabor Filter Approach (GGFA) for object segmentation. An improved and efficient approach based on Gaussian and Gabor Filter reads the given input image and performs filtering and smoothing operation. The region occupied by the object is extracted from the image by performing various operations like bilateral filtering, Edge detection, Clustering, and Region growing. The proposed approach experimented on standard images taken from Caltech datasets, Corel Photo CDs, and Weizmann horse datasets show significantly improved results. | |
| publisher | The American Society of Mechanical Engineers (ASME) | |
| title | Gaussian and Gabor Filter Approach for Object Segmentation | |
| type | Journal Paper | |
| journal volume | 14 | |
| journal issue | 2 | |
| journal title | Journal of Computing and Information Science in Engineering | |
| identifier doi | 10.1115/1.4026458 | |
| journal fristpage | 21006 | |
| journal lastpage | 21006 | |
| identifier eissn | 1530-9827 | |
| tree | Journal of Computing and Information Science in Engineering:;2014:;volume( 014 ):;issue: 002 | |
| contenttype | Fulltext | |