Fu Z Q, Zhang X L, Yu C, et al. Cylindrical image mosaic method based on fast camera calibration in multi-scene[J]. Opto-Electron Eng, 2020, 47(4): 190436. doi: 10.12086/oee.2020.190436
Citation: Fu Z Q, Zhang X L, Yu C, et al. Cylindrical image mosaic method based on fast camera calibration in multi-scene[J]. Opto-Electron Eng, 2020, 47(4): 190436. doi: 10.12086/oee.2020.190436

Cylindrical image mosaic method based on fast camera calibration in multi-scene

    Fund Project: Supported by National Natural Science Foundation of China (51805280), the Public Technology Application Project of Zhejiang (2017C31094), and Natural Science Foundation of Zhejiang (LQ18E050005)
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  • A cylindrical image mosaic method based on fast camera calibration in multi-scene is proposed to solve the problems of scene limitation and complex calibration process in image mosaic using camera calibration parameter. Firstly, the accurate corner feature of checkerboard calibration board is used to make it in the overlapping field of view of two adjacent images. Then, the image sequence is pre-processed by corner extraction, precision and matching, so that the registration parameters between the images to be stitched can be solved accurately and quickly. After that, the cylindrical projection is used to maintain the visual consistency of the images, and the multi-band fusion is used to retain the details of the images. Subsequently, the images are stitched using registration parameters obtained by calibration. Finally, the whole system is built on a low-power embedded platform to accomplish fast calibration and mosaic process based on calibration parameters in multi-scene. The experiment results show that the proposed method can accomplish camera calibration quickly and accurately in indoor and tunnel scenarios, and the image mosaic process is time-consuming. Meanwhile, it can ensure better stitching accuracy and imaging effect, and has strong robustness.
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  • Overview: Image mosaic is the process of combining two or more images with an overlapping field of view in the same scene to produce a seamless panorama or high-resolution image. The image obtained by mosaic has a larger field of view (FOV). Most of the cameras have a FOV angle of about 35 × 50 degrees, which limits the acquisition of information. Therefore, through image mosaic, the continuous image sequence of the same scene is stitched to form a composite image with a larger FOV, which can obtain all visual information at a given point of view at one time. This technology plays an important role in many fields, such as geological survey, medical minimally invasive surgery, and virtual reality. Its technical advantages are obvious. Researchers at home and abroad have done a lot of researches on image mosaic, and image registration is the key step. At present, there are mainly three classical registration methods based on frequency domain, gray level, and feature points, respectively. Nevertheless, the above image registration algorithms generally have the problems of large computational load and low execution efficiency. In this regard, some domestic researchers have proposed a camera calibration method, which saves most of the time needed for stitching and achieves high stitching accuracy.

    But at present, the mosaic algorithm based on camera calibration is limited by the scene, and the calibration process is complex. The collinear condition in imaging will be destroyed after image transformation, which is not conducive to subsequent image processing and information classification. For this reason, a cylindrical image mosaic method based on fast camera calibration in multi-scene is proposed. This method makes full use of the high accuracy of feature extraction of checkerboard calibration board, which is used to make it in the overlapping field of view of two adjacent images. In order to accurately and quickly solve the registration parameters between the images to be spliced, the image sequence is pre-processed by corner extraction, precision and matching. Then, cylindrical projection and multi-band fusion are used to maintain visual consistency and detailed information. The system is based on a Low-Power Embedded platform, which achieves fast acquisition and accurate mosaic of camera calibration parameters in multi-scene. The experiment results show that the proposed method can accomplish camera calibration quickly and accurately in indoor and tunnel scenarios, and the image mosaic process is time-consuming. Meanwhile, it can ensure better stitching accuracy and imaging effect, and has strong robustness.

    The proposed method has positive significance for real-time image stitching without feature points or large environmental changes.

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