Abstract

In this research, we aim to propose an image sharpening method to make it easy to identify concrete cracks from blurred images captured by a moving camera. This study is expected to help realize social infrastructure maintenance using a wide range of robotic technologies, and to solve the future labor shortage and shortage of engineers. In this paper, a method to estimate parameters of motion blur for Point Spread Function (PSF) is mainly discussed, where we assume that there are two main degradation factors caused by the camera, out-of-focus blur and motion blur. A major contribution of this paper is that the parameters can properly be estimated from a sub-image of the object under inspection if the sub-image contains uniform speckled texture. Here, the cepstrum of the sub-image is fully utilized. Then, a filter convoluted PSF which consists of convolution with PSF (motion blur) and PSF (out-of focus blur) can be utilized for deconvolution of the blurred image for sharpening with significant effect. PSF (out-of-focus blur) is a constant function unique to each camera and lens, and can be confirmed before or after shooting. PSF (motion blur), on the other hand, needs to be estimated on a case-by-case basis since the amount and direction of camera movement varies depending on the time of shooting. Previous research papers have sometimes encountered difficulties in estimating the parameters of motion blur because of the emphasis on generality. In this paper, the main object is made of concrete, and on the surface of it there are speckled textures. We hypothesized that we can narrow down the candidates of parameters of motion blur by using these speckled patterns. To verify this hypothesis, we conducted experiments to confirm and examine the following two points using a general-purpose camera used in actual bridge inspections: 1. Influence on the cepstrum when the isolated point-like texture unique to concrete structures is used as a feature point. 2. Selection method of multiple images to narrow down the candidate minima of the cepstrum. It is novel that the parameters of motion blur can be well estimated by using the unique speckled pattern on the surface of the object.

Highlights

  • We conducted experiments to confirm and examine the following two points using a general-purpose camera [4] used in actual bridge inspections: 1. Influence on the cepstrum when the isolated point-like texture unique to concrete structures is used as a feature point. and 2

  • Images acquired by a camera mounted on a mobile object are subject to degradation, such as blurring of the camera focus due to shooting in dark areas or blurring of the acquired images due to shooting while a mobile robot is moving, which makes it difficult to check for cracks and other damages necessary for the maintenance of concrete structures

  • In order to realize bridge inspection using a camera mounted on a mobile object such as a drone, it is desirable to estimate the Point Spread Function (PSF) that causes blurring and to estimate the original image using the R-L algorithm or other methods

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Summary

Introduction

It is difficult to secure the engineers necessary for these inspections; the number of engineers is insufficient for bridge inspection in 20 percent of local governments in Japan. It is desired to realize bridge inspection using a camera mounted on a mobile object such as a drone or a mobile robot in order to solve the future labor shortage and shortage of engineers and improve the efficiency of inspections [3]. In order to obtain information necessary for maintenance from the images acquired by the camera, the camera can be mounted on a mobile object such as a drone or a mobile robot. The motivation of this research is to realize bridge inspection managed by the national and local governments using a general-purpose camera mounted on a mobile object such as a drone or a mobile robot

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