Abstract The H.E.S.S. Galactic Plane Survey [HGPS, 1] represents one of the most sensitive surveys of the Galactic Plane at very high energies (VHE, 0.1 Our goal is to build in a short amount of computational time a list of potentially valuable objects without prior case-specific morphological assumptions. We aim to classify and rank the detected objects in order to identify only the most promising source candidates for further multi-wavelength-association searches, dedicated analyses, or deeper observations. In the approach proposed, we extract sparse and pertinent structural information from the significance maps using a edge detection operator. We then apply a Hough circle transform and detect a collection of objects as local maxima in the Hough space. On the basis of morphological parameters we can characterize different object classes. Classification can be used to identify valuable source candidates sharing the characteristics of well-known sources. We show that using these pattern recognition techniques we can detect objects with partial circular symmetry irrespective of a morphological template (e.g. point-like, Gaussian-like, or shell-like). All the shell-type supernova remnants (SNRs) catalogued in the HGPS (from dedicated analyses) are associated with at least one detected object. Catalogue cross-matches indicate that several detected objects not catalogued in the HGPS are spatially coincident with multi-wavelength counterparts. This paper can be seen as a prospective study for the search of VHE γ-ray sources based on Hough transform and morphological classification. The algorithm have been tested on bootstrap simulations and applied to significance maps of the H.E.S.S. Galactic survey. Further investigation on the most promising candidates will be conducted in dedicated follow-up analyses.

中文翻译：

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基于模式识别的高能源搜索展望 HESS银河平面巡天和目录交叉匹配中的目标检测

分类可用于识别具有知名来源特征的有价值的候选来源。我们表明，使用这些模式识别技术，我们可以检测具有部分圆对称性的对象，而无需考虑形态模板（例如点状、高斯状或壳状）。在 HGPS 中编目（来自专门分析）的所有壳型超新星遗迹 (SNR) 都与至少一个检测到的物体相关联。目录交叉匹配表明，未在 HGPS 中编目的几个检测到的物体与多波长对应物在空间上重合。本文可以看作是基于霍夫变换和形态学分类搜索VHE γ射线源的前瞻性研究。该算法已经在 bootstrap 模拟上进行了测试，并应用于 HESS 的显着性图 银河调查。将在专门的后续分析中对最有希望的候选人进行进一步调查。