关键词: Hadoop, 高分辨率图像, 缺陷检测, MapReduce

Abstract: Various types of defects would come into being in the process of producing 6th TFT-LCD. There are bottlenecks of storing resources and calculating time by inspecting defects with one single machine. It is a new way to deal with massive high-resolution LCD images by Hadoop clusters, which has the advantage in computing and storage capacity. Since the defect is a local feature of high-resolution LCD image, a distributed method of defect inspection based on MapReduce framework is proposed in this paper. To solve the problem of low efficiency of high-resolution image in defect inspection, the approach can be simply described as follows. First, the high-resolution image is split into multiple small splits, which are parallel inspected in the following step. In the final step, the intermediate results are aggregated to obtain the final result. The experimental results show that this approach can inspect defects simultaneously on Hadoop cluster with a good speed up rate.

Key words: Hadoop, high-resolution image, defect inspection, MapReduce