《外文翻译-一种有效地自动图像增强方法》-毕业论文设计（学术).doc

附录A：外文文献 An Effective Automatic Image Enhancement Method ABSTRACT Otsu method is proper to deal with two conditions: (1) two or more classes with distintive gray-values respectively; (2) classes without distinctive gray-values, but with similar areas. However, when the gray-value differences among classes are not so distinct, and the object is small relative to backgroud, the separabilities among classes are insufficient. In order to overcome the above problem, this paper presents an improved spatial low-pass filter with a parameter and presents an unsupervised method of automatic parameter selection for image enhancement based on Otsu method. This method combines image enhancement with image segmentation as one procedure through a discriminant criterion. The optimal parameter of the filter is selected by the discriminant criterion given to maximize the separability between object and background. The optimal threshold for image segmentation is computed simultaneously. The method is used to detect the surface defect of container. Experiments illustrate the validity of the method. KEYWORDS image processing; automated image enhancement; image segmentation; automated visual inspection 1 Introduction Automated visual inspection of cracked container (AVICC) is a practical application of machine vision technology. To realize our goal, four essential operations must be dealt with – image preprocessing, object detection, feature description and final cracked object classification. Image enhancement is to provide a result more suitable than original image for specific applications. In this paper the objective of enhancement, followed by image segmentation, is to obtain an image with a higher content about the object interesting with less content about noise and background. Gonzalez [1] discusses that image enhancement approaches fall into two main categories, in that spatial domain and frequency domain methods. Burton [2] applies image averaging technique to face recognition