3D Reconstruction of Fishes Using Coded Structured Light

Abstract

3D reconstruction of fishes provides the capability of extracting geometric measurements, which are valuable in the field of Aquaculture. In this paper, a novel method for 3D reconstruction of fishes using the Coded Structured Light technique is presented. In this framework, a binary image, called pattern, consisting of white geometric shapes, namely symbols, on a black background is projected onto the surface of a number of fishes, which belong to different species. A camera captures the resulting images, and the various symbols in these images are decoded to uniquely identify them on the pattern. For this purpose, a number of steps, such as the binarization of the images captured by the camera, symbol classification, and the correction of misclassifications, are realized. The proposed methodology for 3D reconstructions is adapted to the specific geometric and morphological characteristics of the considered fishes with fusiform body shape, something which is implemented for the first time. Using the centroids of the symbols as feature points, the symbol correspondences immediately result in point correspondences between the pattern and the images captured by the camera. These pairs of corresponding points are exploited for the final 3D reconstructions of the fishes. The extracted 3D reconstructions provide all the geometric information which is related to the real fishes. The experimentation demonstrates the high efficiency of the techniques adopted in each step of the proposed methodology. As a result, the final 3D reconstructions provide sufficiently accurate approximations of the real fishes.

Keywords

• computer vision
• 3D reconstruction
• structured light
• binary pattern