CREATION OF IMAGE MODELS FOR INSPECTING VISUAL FLAWS ON CAPACITIVE TOUCH SCREENS

Abstract

Touch screens (TSs) are commonly applied in many electronic appliances such as smartphones, tablets, etc. Currently, capacitive touch screens (CTSs) are the main touch technology of screen panels due to many excellent electronic properties. Problems exist in inspecting fl aws inlaid in appearances of CTSs with structural patterns. Area fl aws are a type of common visual defect that comprises dust, bubbles, ripple marks, and other fl aws of bigger sizes. These fl aws have the attributes of low contrast, brightness with slow changes, unusual and non-orientation forms, and sometimes both bright and dark fl aws existing at the same time in a region. This paper suggests image models based on transformation fi ltering to inspect the area fl aws on appearances of CTSs. We apply the Haar wavelet transform with fl at zone fi ltering technique to eliminate the structural patterns of background by means of fi ltering an approximate sub-image of a breakdown wavelet domain image. Subsequently, the fi ltered image is reversely transformed to obtain a rebuilt image in spatial domain. Last, the rebuilt image with intensifi ed fl aws can be simply partitioned into three species (black fl aws, gray fl aws, and white background) by using a statistical interval estimation method. Therefore, the intricate area fl aws are precisely identifi ed by the suggested scheme. We contrast our approach with three traditional methods with real samples under complex background and conduct quantitative comparisons. The effectiveness and accuracy of the developed image models are confi rmed by expert assessments, as well as by comparative analysis with the known methods in the fi eld of spatial localizations and production-related effects of fl aw detection.