<![CDATA[Todays, digital image processing is widely used in various fields to facilitate humans in doing work by analyzing videos or images for use in decision making in the industrial world. The use of industrial machine technology is one of the most important factors in efforts to facilitate human work, but an industrial machine is inseparable from work failure that can hinder the production process and cause harm to the industry. This study aims to detect a failure in industrial machinery by using video data of industrial machine movements recorded using a webcam camera Image processing technology has advanced significantly over the last decade. Its application to low-power mobile devices has attracted many research groups in relation to new contexts such as augmented reality, visual search, object recognition, etc. As general purpose computing emerges for embedded GPUs and their programming models such as OpenGL ES 2.0 and OpenCL, mobile processors will gain more parallel computing capabilities. Therefore, adapting these advances to accelerate mobile image processing algorithms has become a hot topic. In this paper, our interest is based on a review of the current challenging tasks associated with mobile image processing using serial and parallel computing in several new application contexts.]]>
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