In this paper, we propose a 3-D measurement method of underwater objects using a fish-eye stereo camera. Sensing in aquatic environments is important to maintain underwater structures and research aquatic lives. A 3-D measurement method of objects in water using a fish-eye stereo camera enables underwater robots to execute its task safely with a wide field of view. However, images taken by fish-eye camera have large distortion following projection model. Also, sensing in aquatic environments meets the difficulty that image distortion occurs by refraction of light due to the difference of refractive indices of air, watertight container and water. As to these problems, we introduce a method to correct fish-eye image and a ray tracing method to remove the effect of refraction. Experimental results show the effectiveness of the proposed method.

In this paper, we propose an efficient estimation method of an omnidirectional camera movement. The proposed method is based on Structure from Motion utilizing a constraint of parallel lines. In an environment having manmade structures, parallel lines can be extracted from an omnidirectional image easily and constantly, because of its wide field of view. Parallel lines provides a valuable constraint for camera movement estimation. The proposed method can estimate 3-D camera movements by solving one degree of freedom problem three times without regard to the number of viewpoints. Experimental results show the effectiveness of our proposed method.

View occluders influence the image quality of a subject when occluders exist between a camera and a subject. For example, a blurred fence image interrupts a subject when an image of a scene is captured by a camera through a fence. In this paper, we propose an automatic removal method of foreground occluders from images using multiple focusing. Our method automatically detects foreground occluder regions by using two images with and without flashlight. The influence of foreground occluders is estimated and overlapping effects of foreground occluders are removed by using multiple focus images. Experimental results show the effectiveness of the proposed method.

In this paper, we propose an assisting system of touch panel operation for people with visual disability. In the system, a user specifies the target button on the panel by verbal input. The system detects the button and user's fingertip by analyzing images obtained through stereo camera. Navigation is made by indicating the direction of the fingertip on the panel through headphones with sound. To construct an efficient navigation method, comparisons were made experimentally concerning to indication of the finger motion direction, choice of navigation sound, and indication of the distance. The effectiveness of the proposed method was verified through experiments.

When an image of a scene is captured by a camera through a fence, a blurred fence image interrupts objects in the scene. In this paper, we propose a method for a fence removal from the image using multiple focusing. Most of previous methods interpolate the interrupted regions by using information of surrounding textures. However, these methods fail when information of surrounding textures is not rich. On the other hand, there are methods that acquire multiple images for image restoration and composite them to generate a new clear image. The latter approach is adopted because it is robust and accurate. Multi-focus images are acquired and "defocusing'' information is utilized to generate a clear image. Experimental results show the effectiveness of the proposed method.

A lot of plumbings such as gas pipes and water pipes exist in public utilities, factories, power plants and so on. It is difficult for humans to inspect them directly because they are long and narrow. Therefore, automated inspection by robots equipped with camera is desirable, and great efforts have been done to solve this problem. However, many of existing inspection robots have to rotate the camera to record images in piping because a conventional camera with a narrow view can see only one direction while piping has a cylindrical geometry. The use of an omni-directional camera that can take images of 360° in surroundings at a time is effective for the solution of the problem. However, the shape measurement is difficult only with the omni-directional camera. Then, in this paper, we propose a reconstruction method of piping shape by using an omni-directional camera and an omni-directional laser with a light section method and a structure from motion analysis. The validity of the proposed method is shown through experiments.

In this paper, we propose a view planning method that plans view points for efficient 3D map building by a mobile robot equipped with two LRFs (laser range finders). The robot searches for effective view points by predicting new measurement domains in the next view points, and then measures distances to obstacles around the robot with LRFs. The 3D map is generated by integrating range information obtained from multiple measurements. Experimental results show the effectiveness of the proposed method.

Sensing in aquatic environments meets the difficulty that, when a camera is set in air behind a watertight glass plate, image distortion occurs by refraction of light at the boundary surface between air and water. This paper proposes an aquatic sensing method to execute three dimensional measurement of objects in water by taking refraction of light into account. The proposed method is based on a monocular stereo technique using a difference of appearance depending on optical paths. Optimization of the angles of refracting surfaces which are key elements of the sensing device is given to realize the accurate measurement. Experimental results show the effectiveness of the proposed method.

In this paper, a new method for 3-D measurement of objects in water is proposed. When observing objects in water through a camera contained in a waterproof housing or observing objects in an aquarium tank filled with preserving liquid, we should solve a problem of light refraction at the boundary surfaces of refractive index discontinuity which gives image distortion. The proposed method uses a space encoding method which does not have a problem of corresponding point detection as a stereo vision system has, and is faster than spot light projection or slit light projection methods. A ray tracing technique solves the problem of image distortion caused by refractive index discontinuity. It should be noted that monochromatic light projection onto objects gives more accurate measurement than white light projection because the refractive index depends on the wavelength of the light. Then, in order to measure colored objects, we should project red, green and blue light patterns onto them separately. Experimental results show the validity of the proposed method.

Map information is important for path planning and self-localization when mobile robots accomplish autonomous tasks. In unknown environments, mobile robots should generate an environment map by themselves. Then, we propose a method for 3D environment modeling by a mobile robot. For environmental measurement, we use a single omni-directional camera. We propose a new estimation method of camera motions for improvement in measurement robustness and accuracy. The method takes advantage of a wide field of view of an omni-directional camera. Experimental results showed the effectiveness of the proposed method.

This paper describes a method for removing adherent noises from image sequences. In outdoor environments, it is often the case that scenes taken by a camera are deteriorated because of adherent noises such as waterdrops on the surface of the lens-protecting glass of the camera. To solve this problem, our method takes advantage of image sequences captured with a moving camera whose motion is unknown. Our method estimates a camera motion only from image sequences, and makes a spatio-temporal image to extract the regions of adherent noises by examining differences of track slopes in cross section images between adherent noises and other objects. Finally, regions of noises are eliminated by replacing with image data corresponding to object regions. Experimental results show the effectiveness of our method.

In this paper, we propose a region extraction method using chromakey with a two-tone checker pattern background. The proposed method solves the problem in conventional chromakey techniques that foreground objects become transparent if they have the same color with the background. The adjacency condition between two-tone regions of the background and the geometrical information of the background grid lines are utilized for extracting foreground objects. Experimental results show the effectiveness of the proposed method.

In this paper, we propose a new three-dimensional (3-D) measurement method of objects in unknown liquid with a stereo vision system. When applying vision sensors to measuring objects in liquid, light refraction is an important problem. Therefore, we estimate refractive indices of unknown liquids by using images of water surface, restore images that are free from refractive effects of the light, and measure 3-D shapes of objects in liquids in consideration of refractive effects. The effectiveness of the proposed method is shown through experiments.

This paper describes a method for removing adherent noises from image sequences. In outdoor environments, it is often the case that scenes taken by a camera are deteriorated because of adherent noises such as waterdrops on the surface of the lens-protecting glass of the camera. To solve this problem, our method takes advantage of image sequences captured with a moving camera. The method makes a spatio-temporal image to extract the regions of adherent noises by examining differences of track slopes in cross section images between adherent noises and other objects. Finally, regions of noises are eliminated by replacing with image data corresponding to object regions. Experimental results show the effectiveness of our method.

Colors of objects observed in underwater environments are different from those in air. This is because the light intensity decreases with the distance from objects in water by light attenuation. Robots on the ground or in air usually recognize surrounding environments by using images acquired with cameras. The same is/will be true of underwater robots. However, recognition methods in air based on image processing techniques may become invalid in water because of light attenuation. Therefore, we propose a color registration method of underwater images. The proposed method estimates underwater environments where images are acquired, in other words, parameters essential to color registration, by using more than two images. After estimating parameters, color registration is executed with consideration of light attenuation. The effectiveness of the proposed method is verified through experiments.

In this paper, we propose a new method for reducing assembly time in printed circuit board (PCB) assembly by prioritizing efficient simultaneous pickup operation of placement machines. Despite using the same placement machine, the efficiency of the schedule results in major different assembly time. Therefore, it is important to optimize the scheduling of component mounting. There are three major problems of the scheduling: (1) component feeder location (affects efficiency of pickup operation), (2) mounting sequencing (affects total distance of the mounting tour) , and (3) simultaneous pickup (affects efficiency of pickup operation). To solve these problems, this paper proposes the following approaches. We solve (1) and (3) in a heuristic way by using a random multi-start local search. We solve (2) greedily with putting the result of the feeder array to effective use. The effectiveness of the proposed method was shown through simulations.

In this paper, we propose robust sensing method against bubble noises in aquatic environments with a stereo vision system. Usually, three-dimensional (3-D) measurement by robot vision techniques is executed under the assumptions that cameras and objects are in aerial environments. However, an image distortion occurs when vision sensors measure objects in liquid. It is caused by the refraction of the light on the boundary between the air and the liquid, and the distorted image brings errors in a triangulation for the range measurement. Additionally, it is often the case that there exist air bubbles in the field of view when we observe aquatic environments. Therefore, it becomes difficult to acquire clear images because of these view-disturbing noises. As to the former problem, accurate 3-D coordinates of objects' surfaces in liquid are measured by taking for calculating the refraction effect. As to the latter problem, bubble noises are eliminated from a moving image to divide objects in the image into still backgrounds, moving objects, and bubble noise by an image processing technique. Experimental results showed the effectiveness of our proposed method

In this paper, we propose a new method that can inspect visual and non-visual features of objects simultaneously by using image and sound signal processing techniques. A method for discriminating a property of an object with the use of generated sound when striking it with a hammer is called a hammering test. This method can investigate non-visual features of objects such as inner structure of objects, e.g., the existence of defects and cracks inside objects. However, this method depends on human experience and skills. In addition, if we perform this test over a wide area of objects, it is required to manually record hammering positions one by one. To solve these problems, this paper proposes a hammering test system consisting of two video cameras that can acquire image and sound signals of a hammering scene. The shape of the object (visual feature) is measured by the image signal processing from the result of 3-D measurement of each hammering position, and the thickness or material (non-visual feature) is estimated by the sound signal processing in time and frequency domains. The validity of proposed method is shown through experiments

In this paper, we propose a three-dimensional (3-D) measurement method of objects in aquatic environments whose refractive indices or boundary shape of the refraction are unknown with a laser range finder. When applying vision sensors to measuring objects in liquid, we meet the problem of an image distortion. It is caused by the refraction of the light on the boundary between the air and the liquid, and the distorted image brings errors in a triangulation for the range measurement. Therefore, 3-D measurement of objects in liquid requires a geometrical analysis that takes refraction effects into account. In the analysis, it is indispensable to know the boundary shapes that have discontinuity of refractive indices, and refractive index of liquid. Our proposed method takes refraction effects into account and estimates these unknown parameters to measure accurate 3-D shapes of objects in liquid. Experimental results have shown the effectiveness of the proposed method.

In this paper, we propose a new method that can remove view-disturbing noises from stereo images. One of the thorny problems in outdoor surveillance by a camera is that adherent noises such as waterdrops on the protecting glass surface lens disturb the view from the camera. Therefore, we propose a method for removing adherent noises from stereo images taken with a stereo camera system. Our method is based on the stereo measurement and utilizes disparities between stereo image pair. Positions of noises in images can be detected by comparing disparities measured from stereo images with the distance between the stereo camera system and the glass surface. True disparities of image regions hidden by noises can be estimated from the property that disparities are generally similar with those around noises. Finally, we can remove noises from images by replacing the above regions with textures of corresponding image regions obtained by the disparity referring. Experimental results show the effectiveness of the proposed method.

In this paper, we propose a three-dimensional (3D) measurement method of objects' shapes in liquid by using the light stripe projection method. Usually, 3D measurement by robot vision techniques is executed under the assumptions that cameras and objects are in aerial environments. However, an image distortion occurs when vision sensors measure objects in liquid. It is caused by the refraction of the light on the boundary between the air and the liquid, and the distorted image brings errors in a triangulation for the range measurement. Our proposed method can measure accurate 3D coordinates of objects' surfaces in liquid taken for calculating the refraction effect. The effectiveness of the proposed method is shown through experiments. By considering the refraction of the light, the accuracy of the 3D measurement of objects in water becomes same as that when there is no water, although the accuracy is bad when the refraction of the light is not considered. The accuracy of the 3D measurement is about 1 mm for objects located about 400 mm from the laser range finder. The measurement speed can be also reduced as compared with the case of using a spot laser beam.

In this paper, we propose a new method that can remove view-disturbing waterdrops from images by processing images taken with a pan-tilt camera system. In rainy days, it is often the case that images taken by the camera are hard to see because of adherent waterdrops on the surface of the protecting glass of the camera. In our method, an image of a distant prospect is taken at first and another image is taken after changing the direction of eyeshot. The new image is transformed with the projective transformation and compared with the first one to detect the region where waterdrops may exist. We can distinguish which image portion belongs to waterdrops by considering the distance between two waterdrop candidate regions. Finally, the region where waterdrops exist can be eliminated to merge two images. Experimental results show the effectiveness of the proposed method.

In this paper, we propose a new path and viewpoint planning method for a mobile robot with multiple observation strategies. When a mobile robot works in the constructed environments such as indoor, it is very effective and reasonable to attach landmarks on the environment for the vision-based navigation. In that case, it is important for the robot to decide its motion automatically. Therefore, we propose a motion planning method that optimizes the efficiency of the task, the danger of colliding with obstacles, and the accuracy and the ease of the observation according to the situation and the performance of the robots. We also introduce multiple landmark-observation strategies to optimize the motion depending on the number and the configuration of visible landmarks in each place.

In this paper, we propose a new method that can remove view-disturbing noises from images of dynamic scenes. One of the thorny problems in outdoor surveillance by a camera is that adherent noises such as waterdrops or mud blobs on the protecting glass surface lens disturb the view from the camera. Therefore, we propose a method for removing adherent noises from images of dynamic scenes taken by changing the direction of a pan-tilt camera, which is often used for surveillance. Our method is based on the comparison of two images, a reference image and a second image taken by a different camera angle. The latter image is transformed by a projective transformation and subtracted from the reference image to extract the regions of adherent noises and moving objects. The regions of adherent noises in the reference image are identified by examining the shapes and distances of regions existing in the subtracted image. Finally, regions of adherent noises can be eliminated by merging two images. Experimental results show the effectiveness of our proposed method.

In this paper, we propose a three-dimensional (3-D) measurement method of objects in liquid with a laser range finder. When applying vision sensors to measuring objects in liquid, we meet the problem of an image distortion. It is caused by the refraction of the light on the boundary between the air and the liquid, and the distorted image brings errors in a triangulation for the range measurement. Our proposed method can measure the accurate 3-D coordinates of objects surfaces in liquid taken for calculating the refraction effect. The effectiveness of the proposed technique is shown through experiments. The accuracy of the 3-D measurement is 0.7 mm for objects located about 250 mm from the laser range finder when considering the refraction of the light, although that is 2.9 mm without the consideration of it.

In this paper, we propose a new method for the restoration of deteriorated images by using multiple cameras. In outdoor environment, it is often the case that scenes taken by the cameras are hard to see because of adherent noises on the surface of the lens-protecting glass of the cameras. Our proposed method analyses multiple camera images describing the same scene, and synthesizes an image in which adherent noises are eliminated.

The paper proposes a generation system of unit quarternion curves and surfaces to design fair curves and surfaces. Curvature and variation of curvature are the primary factors that determine the quality of fair curves and surfaces; however not so many methods have been explored to directly manipulate them, especially in three dimensional space. We use unit quaternion curves in integral forms to specify the tangent of a curve and the first derivative of a surface in one parameter direction. This enables us to control their curvature and variation of curvature more than is possible with traditional parametric representations like Bezier and NURBS curves and surfaces. Using unit quaternion curves balances the efficiency of the design process and the fairness of the designed curves and surfaces. Our system can generate fair curves and surfaces within a short time and their quality is acceptable for industrial applications as well as CG animation.

An efficient encoding scheme for arbitrary curves, based on the chain code representation, has been proposed. The encoding scheme takes advantage of the property that a curve with gentle curvature is divided into somewhat long curve sections (segments), each of which is represented by a sequence of two adjacent-direction chain codes. The coding efficiency of the scheme becomes higher as the segments become longer, while a variable-length coding technique makes it possible to encode short segments without an extreme increase in code amount. An experiment with complicated curves obtained from geographic maps has shown a high data compression rate of the proposed scheme, whose code amount is about 50-60 percent of that required for the conventional chain encoding scheme.