Defect Detection in Random Color Textures using the Modified MIA T2 Defect Maps

سال انتشار: 1385
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 2,161

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شناسه ملی سند علمی:

ICMVIP04_094

تاریخ نمایه سازی: 21 دی 1386

چکیده مقاله:

In this paper we present a new unsupervised approach for the detection of defects in random color textures. This approach is based on the use of the 2 T statistic and it is derived from the MIA strategy (Multivariate Image Analysis) developed in recent years in the field of applied statistics. PCA analysis is used to extract a reference eigenspace from a matrix built by color-textural features of partially overlapped windows or patches inside the input RGB image. For each window of size L L ´ the mean and the variance of each chromatic channel extracted as color features. Also, a compressed version of LBP histograms is used to extract the textural information of each patch. These extracted features make the columns of a data matrix. The same task is performed for each new testing image and the obtained data matrix is projected onto the reference eigenspace obtaining a score matrix used to compute the 2 T images. These obtained images are then converted into defect maps which allow localizing of defective pixels. We present some results from a database of images of artificial stone plates and ceramic tiles.

نویسندگان

Hadi Hadizadeh

Departmant of Electrical and Electronic Engineering Iran University of Science and Technology(IUST)

Fernando Lopez

Department of Computer Science(DISCA) Technical University of Valencia (UPV)

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