Texture classification using structured artificial neural network
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Detail(s)
| Original language | English |
|---|---|
| Pages (from-to) | 397-402 |
| Journal / Publication | Artificial Neural Networks in Engineering - Proceedings (ANNIE'94) |
| Volume | 4 |
| Publication status | Published - 1994 |
Conference
| Title | Proceedings of the Artificial Neural Networks in Engineering Conference (ANNIE'94) |
|---|---|
| City | St. Louis, MO, USA |
| Period | 13 - 16 November 1994 |
Link(s)
Abstract
The spatial gray level dependence (SGLD) method is one of classification the algorithms for image classification. In this paper, described is an alternative method, artificial neural network (ANN) to implement this algorithm. A structured artificial neural network with three subnetworks is proposed to estimate the SGLDM algorithm. The complete system is tested using glass, bark, herringbone-weave, plastic bubble and brick textures. The overall classification accuracy is over 92%.
Citation Format(s)
Texture classification using structured artificial neural network. / Ko, N. Y.; Lee, Alex W H; Cheng, L. M.
In: Artificial Neural Networks in Engineering - Proceedings (ANNIE'94), Vol. 4, 1994, p. 397-402.
In: Artificial Neural Networks in Engineering - Proceedings (ANNIE'94), Vol. 4, 1994, p. 397-402.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
