Advanced image stitching method and evaluation for underwater structure inspection utilizing planar array cameras

The inspection of underwater structural health is crucial for comprehensive bridge health assessments. In underwater structure imaging, traditional methods include single-camera and binocular camera inspection. However, due to water turbidity and long working distances with a small field-of-view, obtaining clear and high-quality detection images with these methods takes much work. To address this problem, this paper presents a method for planar array image stitching based on Harris corner point extraction, utilizing the advantages of planar array cameras characterized by short working distances and wide field-of-view. The core contribution of this paper is the introduction of an innovative image sequence stitching algorithm utilizing Harris corner point extraction and the combination of the first proposed planar array cameras with the image sequence stitching algorithm, which solves the problem of long distance and small field-of-view during the underwater inspection. The image stitching method involves calibrating camera parameters with a checkerboard and stitching underwater images from planar array cameras to reveal underwater structural features. Furthermore, five quantitative evaluation metrics and the method for calculating the field-of-view loss rate are presented to evaluate and analyze the stitched images. A series of experiments were performed on concrete surfaces, aquatic and underwater, with a total field-of-view of the underwater image after stitching of 358.86 mm × 319.24 mm at a working distance of 160 mm. Five evaluation methods were used to quantitatively evaluate the quality of the stitched images and calculate the field-of-view loss rate of the images. The results indicate that the proposed method improves the ability to inspect underwater. The stitched images achieve notable metrics: an entropy of approximately 6.7, an average gradient of about 1.7, a spatial frequency of around 3.5, an edge strength of about 17, mutual information of approximately 1.2, and a field-of-view loss rate of <0.1, facilitating more effective underwater structure inspection.