Development of an Automatic Testing Platform for Aviator’s Night Vision Goggle Honeycomb Defect Inspection

Abstract

Due to the direct influence of night vision equipment availability on the safety of night-time aerial reconnaissance, maintenance needs to be carried out regularly. Unfortunately, some defects are not easy to observe or are not even detectable by human eyes. As a consequence, this study proposed a novel automatic defect detection system for aviator’s night vision imaging systems AN/AVS-6(V)1 and AN/AVS-6(V)2. An auto-focusing process consisting of a sharpness calculation and a gradient-based variable step search method is applied to achieve an automatic detection system for honeycomb defects. This work also developed a test platform for sharpness measurement. It demonstrates that the honeycomb defects can be precisely recognized and the number of the defects can also be determined automatically during the inspection. Most importantly, the proposed approach significantly reduces the time consumption, as well as human assessment error during the night vision goggle inspection procedures.

Multifocus Image Fusion Using a Sparse and Low-Rank Matrix Decomposition for Aviator’s Night Vision Goggle

“…In order to simplify and facilitate the description of subsequent algorithms, the images collected were converted from colored ones into the gray-level, 110 images in total for autofocusing the algorithm used. To compare the quality of the traditional methods with the method in this paper, the same image sources as those of Jian and Peng [1] were used.…”

“…After the focus adjustment operation is completed, to make sure that the equipment is in line with calibration standards is confirmed only by human eyes. Since automatic image detection technology is sophisticated and widely applied, the researcher aims to reduce the staff's education time and to achieve the goal of proper equipment used by means of automatic image detection [1]. After gaining an insight into the performance and limitations of NVG, the autofocus operating process can be more accurately developed.…”

“…Therefore, this project intends to use a direct current (DC) servo driver to promote the focal knob of NVG to achieve the purpose of adjusting focus and acquiring quantitative value of rotation angle. For the configuration and design, refer to the document [1]. At present the autofocusing methods can be divided into active autofocusing and passive autofocusing [4].…”

“…Light luminance is the key affecting the passive autofocusing system. In previous studies, many types of sharpness computing methods were compared [5] to determine merits and drawbacks, which were applied in NVG's autofocusing [1]. In passive autofocusing, regardless of sharpness computing method, the subsequent image intensifier display on the screen undergoes defect testing, all of which are independent processes.…”

“…In passive autofocusing, regardless of sharpness computing method, the subsequent image intensifier display on the screen undergoes defect testing, all of which are independent processes. Jian and Peng proposed autofocusing process for NVGs [1], which uses gradient-based variable step search and variation of normalized gray-level as the main method for accomplishing autofocus. Wang et al [6] suggested the application of a robust principal component analysis method in multifocus image fusion.…”