针对复杂环境下图像分析的困难性，研究了一种基于HSV 空间模型的图像分割与检测方法。首先，利用无人机采集图像，区域分割提取出光伏电池板区域。其次，运用高斯卷积检测裂纹图像的梯度。最后，应用形态学图像处理与HSV 空间模型的方法提取遮挡物，计算最小外接矩形面积与其占光伏电池板的比例。该方法能有效地对复杂背景下的光伏图像进行区域分割与检测，具有一定创新性和实用价值。

To address the difficulty of image analysis in a complex environment, an image segmentation and detection method of an HSV spatial model was studied. First, a UAV was used to collect images. Second, Gaussian convolution was used to detect the gradient of the cracked image after the photovoltaic(PV) panel area was extracted. Finally, morphological image processing and the HSV spatial model were applied to extract the occlusion, and the ratio of the minimum external rectangle area to the PV panel area was calculated. This method can effectively segment and detect PV images in complex backgrounds and provides certain innovative and practical value.