A Dual Domain Approach for Surface Roughness Evaluation
- Resource Type
- Conference
- Authors
- Bhandari, Smriti H.; Deshpande, S.M.
- Source
- International Conference on Computational Intelligence and Multimedia Applications (ICCIMA 2007) Conference on Computational Intelligence and Multimedia Applications, 2007. International Conference on. 3:344-348 Dec, 2007
- Subject
- Computing and Processing
Signal Processing and Analysis
Rough surfaces
Surface roughness
Wavelet transforms
Surface texture
Milling
Casting
Wavelet domain
Surface waves
Data mining
Image edge detection
- Language
The research presented in this paper is aimed at developing an automated imaging system for classification of engineered surfaces with appropriate roughness measures. The method uses dual domain of Radon transform and Wavelet transform. Radon transform helps to locate directional information of surface textures whereas wavelet transform is used to compute features from textures. To extract significant information from textures we first employ Canny edge detection to texture image and then undergo radon and wavelet transformation. Further we carryout the process on a set of four images original and rotated to form the robust feature set. Our feature vector has 36 features. Experimentation is carried out on three surface texture databases manufactured by machining processes milling, casting and shaping. We achieved 95.56% correct classification performance for milling samples where as 67.04% for casting and 87.08% for shaping samples.