Chen Fengdong

Segmentation of small defects in Final Optics Damage Online Inspection images

Automotive detection of defects plays an important role in Final Optics Damage Online Inspection (FODOI). Because of the tiny size of defects compared to the image, detection of the defects is a challenge. In a 2k×2k FODOI image, the size of the defects is only several pixels. Moreover, the gray value of different image areas is different because of the uneven distribution of illumination. In this paper, a robust defects detecting method based on Local Area Signal Strength (LASS) and 2-D histogram is theoretically and experimentally proposed. After the image stretching process achieved by grayscale morphology arithmetic, we computed the LASS at every pixel in the image, resulting in a new image with LASS values for each pixel. Thus, an adaptive threshold selection algorithm in 2-D histogram formed by LASS was achieved. The proposed algorithm was compared with some other fast algorithms, such as the traditional 2-D histogram algorithm, Otsu algorithm, and the FCM clustering algorithm; the results show that the proposed algorithm has higher detection precision and is robust in uneven illumination.

Dots-array photogrammetry of flexible antenna surfaces

The paper proposes a method of using dots in an array as targets for photogrammetry to reconstruct the surface of a large-size flexible antenna efficiently. An analysis demonstrates the impacts of the spot size and the regional feature on the point extraction accuracy, and introduces a fitting-ellipse algorithm in this paper that eliminates the deformation and the shielding. In the feature extraction and matching processes, this article puts forward a feature identification technique based on the area and a matching algorithm depending on the order constraint. The paper closes with an experiment that shows the equipment that can measure a gossamer area of 1m×1.2m in time of less than 1s, which shows its advantages of high accuracy and high efficiency in detecting the shape of a large field.