The main challenges of 骨架提取 (skeleton extraction) are as follows:

  1. Noise and Imperfections: Image data often contains noise, artifacts, and imperfections that can affect the accuracy of skeleton extraction algorithms. These abnormalities can disrupt the continuity of the skeleton and lead to errors in its extraction.

  2. Image Resolution: Low-resolution images can make it difficult to accurately extract the skeleton. The lack of detail and fine structures in such images can result in incomplete or fragmented skeletons.

  3. Image Complexity: Complex images with overlapping structures, occlusions, or varying background intensities pose challenges for 骨架提取. These complexities can make it hard to distinguish between foreground and background, leading to inaccurate or incomplete skeleton extraction.

  4. Thickness Variation: Objects with varying thickness in the image can complicate skeleton extraction. Determining the correct skeleton when objects have regions with different thicknesses requires sophisticated algorithms that can handle such variations.

  5. Branching Structures: Skeleton extraction becomes challenging when dealing with branching structures such as blood vessels or tree branches. Accurately capturing the intricate details of these structures and determining their connectivity is a complex task.

  6. Computational Complexity: Efficient skeleton extraction algorithms are required to handle large image datasets in a reasonable amount of time. As the size of the image increases, the computational requirements for skeleton extraction can become prohibitive.

  7. Object Connectivity: In cases where objects in the image are closely connected, extracting individual skeletons without merging or overlapping becomes difficult. Careful consideration is needed to separate and extract the skeletons accurately.

  To overcome these challenges, researchers have developed various techniques and algorithms for 骨架提取, including morphological operations, graph-based methods, and machine learning approaches. It is an active research area with ongoing efforts to improve the accuracy and efficiency of skeleton extraction algorithms.