Automatic functional TV set failure detection system

Abstract

Enormous technological innovation in recent years has put a great challenge upon manufacturers in consumer electronics industry: how to efficiently and accurately verify the functionality of a product handed to a customer. To address this problem, we propose a fully automated system for functional failure detection in TV sets. In the proposed framework, the automatic assessment of TV set functionality is performed by processing captured images of the TV set under inspection and the captured images from the reference TV set (which is considered to be with no functional failures). A new algorithm for image similarity is proposed and incorporated in the system for evaluating the difference between the tested image and the reference one, in respect to specific degradations that can occur in TV sets. The similarity detection algorithm is a full-reference intra-frame video quality assessment scheme, which is based on spatially local mean square error and variance between the reference and the tested image. Based on the similarity detection, an acceptance decision for the TV set functionality is made. The proposed embedded system for automatic TV functional failure detection includes (i) central control unit through which the testing methodology is carried out: The TV set under inspection is fed by the test video signals defined by the (ii) specified test-case-scenario, while the picture is simultaneously captured from the tested TV set and compared by the (iii) proposed similarity detection algorithm to the reference one, for the same type of TV set. Finally, the results are stored in the (iv) data base for TV set debugging purposes. The usability and effectiveness of the proposed methodology has been experimentally evaluated and detailed analysis of the results has been reported. The proposed similarity detection algorithm has shown to be superior to the other state-of-the-art image quality assessment algorithms in terms of detecting TV picture degradations (such as picture misalignment, illumination change, aliasing, blurring, etc.) in captured images from TV set, under the methodology which incorporates defined test-case-scenario.