Segmentation plays an important role in the pattern recognition and image processing areas. Several techniques have been proposed aiming at solving generic issues or particular applications. Traditionally, these techniques have been evaluated by using the Overlap measure, which verifies the coincident and non-coincident areas between the image resulting from a segmentation process and an image considered correct. Albeit widely, this type of measure does not allow flexibility in the assessment process. We here propose an approach to evaluate segmentation techniques using concepts from content-based image retrieval and considering a methodology for testing generic programs with graphical outputs, named graphic oracle. Our approach was applied to evaluate the segmentation of mammographic images, and the results indicate a performance compatible with the traditional measure with more flexibility and precision. Thus, our approach provides a contribution to allow a more flexible segmentation assessment, according to image characteristics and application objectives.

中文翻译：

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应用图形预言机评估图像分割结果

分割在模式识别和图像处理领域发挥着重要作用。已经提出了几种旨在解决一般问题或特定应用程序的技术。传统上，这些技术是通过使用重叠测量来评估的，该测量验证由分割过程产生的图像与被认为正确的图像之间的重合和非重合区域。尽管范围很广，但这种类型的措施不允许在评估过程中具有灵活性。我们在这里提出了一种使用基于内容的图像检索概念来评估分割技术的方法，并考虑了一种用于测试具有图形输出的通用程序的方法，称为图形预言机。我们的方法被应用于评估乳房 X 线图像的分割，结果表明性能与传统测量兼容，具有更大的灵活性和精度。因此，我们的方法有助于根据图像特征和应用目标进行更灵活的分割评估。