Parquet Sorting and Grading Based on Color and Texture Analyses

Abstract

In this paper a computer vision algorithm for automatic parquet slab sorting is described, as a part of a real time automatic parquet slab sorting system. Various computer vision algorithms and methods for automatic visual inspection and automatic classification have been analyzed. Developed algorithm consists of three main stages: color analysis, texture analysis and defects detection. The color analysis is based on the percentile values obtained from the cumulative histogram of the image and texture analysis is based on the second order statistical features obtained from gray level co-occurrence matrix. Detection of defects is implemented as the segmentation method, based on the adaptive binary threshold algorithm, which is based on a local square regions and connected component analysis methods. This way we have achieved a very accurate classifying process with about 90 percent of accuracy, which greatly outstands results of human inspector, that are about 60-70 percent.