Automatic inspection of textured surfaces by support vector machines
2009
Automatic inspection of manufactured products with natural looking textures is a challenging task. Products
such as tiles, textile, leather, and lumber project image textures that cannot be modeled as periodic or otherwise
regular; therefore, a stochastic modeling of local intensity distribution is required. An inspection system to
replace human inspectors should be flexible in detecting flaws such as scratches, cracks, and stains occurring
in various shapes and sizes that have never been seen before. A computer vision algorithm is proposed in this
paper that extracts local statistical features from grey-level texture images decomposed with wavelet frames into
subbands of various orientations and scales. The local features extracted are second order statistics derived from
grey-level co-occurrence matrices. Subsequently, a support vector machine (SVM) classifier is trained to learn
a general description of normal texture from defect-free samples. This algorithm is implemented in LabVIEW
and is capable of processing natural texture images in real-time.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
22
References
5
Citations
NaN
KQI