Detection of Carbon Composition in hypo-eutectoid steel based on color texture of Iron-Carbon image
| Author(s) | : | Mr. Sharadchandra M. Kawale, Dr. Anilkumar N. Hohambe |
| Institution | : | Department of Computer Science & Engineering, College of Engineering, Osmanabad |
| Published In | : | Vol. 4, Issue 7 — July 2017 |
| Page No. | : | 593-596 |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
The fundamental data clustering problem may be defined as the process of grouping the data objects intoclasses or clusters, so that objects within a cluster have high similarity in comparison to one another but are verydissimilar to objects in other clusters. This paper proposes solution to find percentage of carbon contents in hypoeutectoid steel through extraction of color futures of various images. A color quantization is focuses on color as featureand considers HVS space. Image pixel color is quantized into number of colors and histogram of these colors hascalculated. To form clusters of images k-means algorithm is applied and proposed solution for finding carbonpercentages in hypo-eutectoid steel.
Mr. Sharadchandra M. Kawale, Dr. Anilkumar N. Hohambe, “Detection of Carbon Composition in hypo-eutectoid steel based on color texture of Iron-Carbon image”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 4, Issue 7, pp. 593-596, July 2017.
