🤖 AI Summary
This work proposes an efficient visual reconstruction system for industrial pipeline interiors, addressing the common limitations of low efficiency and incomplete information in existing approaches. Leveraging a custom-built industrial endoscope, the system employs a self-developed graphical user interface to extract key frames from circular video sequences. An innovative fusion of polar coordinate transformation and image stitching techniques is then applied to unwrap these frames into high-fidelity planar panoramic images. This method substantially enhances both reconstruction efficiency and completeness while preserving fine-grained surface details of the pipe interior. The resulting panoramas provide intuitive and accurate visual support for defect detection and condition assessment, demonstrating strong engineering practicality alongside technical innovation.
📝 Abstract
Visual analysis and reconstruction of pipeline inner walls remain challenging in industrial inspection scenarios. This paper presents a dedicated reconstruction system for pipeline inner walls via industrial endoscopes, which is built on panoramic image stitching technology. Equipped with a custom graphical user interface (GUI), the system extracts key frames from endoscope video footage, and integrates polar coordinate transformation with image stitching techniques to unwrap annular video frames of pipeline inner walls into planar panoramic images. Experimental results demonstrate that the proposed method enables efficient processing of industrial endoscope videos, and the generated panoramic stitched images preserve all detailed features of pipeline inner walls in their entirety. This provides intuitive and accurate visual support for defect detection and condition assessment of pipeline inner walls. In comparison with the traditional frame-by-frame video review method, the proposed approach significantly elevates the efficiency of pipeline inner wall reconstruction and exhibits considerable engineering application value.