• 제어로봇시스템학회:학술대회논문집
• /
• 1995.10a
• /
• pp.299-302
• /
• 1995

Recently, we proposed a 3-D range-image measuring system for a slowly moving object by mechanically scanning a laser light beam emitted from a self mixing laser diode. In this paper, we introduced that every object moves along a straight line course, which is set diagonally against the semiconductor laser beam so that we can recognize each shape and size parameters of objects separately from the acquired 3-D range-image. We measured a square mesa on a square plane as an object. The measured velocity was 4.44mm/s and 4.63mm/s with an error of 0.56mm/s to 0.37mm/s. And thickness error of the mesa was 0.5mm to 0.6mm, which was obtained from the 3-D range-image of the standstill or moving object with thickness of 17.Omm.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.10
• /
• pp.1448-1451
• /
• 2021

In this paper, 3D range sensor is applied to the sensor-based widerange microphone system for lectures. Since the 2D range sensor measures the shortest distance of the speaker, an error occurs and the performance is degraded. The 3D sensor provides a 160×60 distance image so that the position of the speaker can be obtained with accuracy. We propose a method for obtaining the distance per pixel required to determine the absolute position of the speaker from the distance image. The proposed array microphone system using the 3D sensor shows the improvement of 0.8~1.5dB compared to the previous works using 2D sensor.

• Journal of Broadcast Engineering
• /
• v.9 no.1
• /
• pp.64-73
• /
• 2004

A robust watermarking algorithm is proposed for 3D mesh models. Watermark is inserted into the 2D image which is extracted from the target 3D model. Each Pixel value of the extracted 2D image represents a distance from the predefined reference points to the face of the given 3D model. This extracted image is defined as “range image” in this paper. Watermark is embedded into the range image. Then, watermarked 3D mesh is obtained by modifying vertices using the watermarked range Image. In extraction procedure, the original model is needed. After registration between the original and the watermarked models, two range images are extracted from each 3D model. From these images. embedded watermark is extracted. Experimental results show that the proposed algorithm is robust against the attacks such as rotation, translation, uniform scaling, mesh simplification, AWGN and quantization of vertex coordinates.

• Journal of the Korea Computer Graphics Society
• /
• v.3 no.1
• /
• pp.23-28
• /
• 1997

We reconstruct 3D surface from range image that consists of range map and texture map, and simplify the reconstructed triangular mesh. In this paper, we introduce fast simplification method that is able to glue texture to 3D surface model and adapt to real-time multipled level-of detail. We will verify the efficiency by applying to the scanned data of Korean relics.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.93-96
• /
• 1996

Structured laser light is a widely used method for obtaining 3D range information in Machine Vision. However, The structured laser light method is based on assumption that the surface of objects is Lambertian. When the observed surfaces are highly specularly reflective, the laser light can be detected in various parts on the image due to a specular reflection and secondary reflection. This makes wrong range data and the image sensor unusable for the specular objects. To discriminate wrong range data from obtained image data, we have proposed a new algorithm by using the cross section of image block. To show the performance of the proposed method, a series of experiments was, carried out on: the simple geometric shaped objects. The proposed method shows a dramatic improvement of 3D range data better than the typical structured laser light method.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.48 no.5
• /
• pp.658-663
• /
• 1999

2D sliced CT images hardly express the human disease in a space. This space expression can be reconstructed into 3D image by piling up the CT sliced image in succession. In medical image, in order to get the reconstructed 3D images, expensive system or much calculation time is needed. But by changing the method of reconstruction procedure and limit the range, the reconstruction time could be reduced. In this study, to reduce the processing time and memory, we suggested a method of interpolation and ray casting processing at the same time in a limited range. Such a limited range processing have advantages that we could reduce the unnecessary interpolation and ray casting. Through a experiment, it is founded that the reconstruction time and the memory was much reduced.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.1177-1179
• /
• 2003

Recently, the ground-based laser profiler is used for acquisition of 3D spatial information of a rchaeological objects. However, it is very difficult to measure complicated objects, because of a relatively low-resolution. On the other hand, texture mapping can be a solution to complement the low resolution, and to generate 3D model with higher fidelity. But, a huge cost is required for the construction of textured 3D model, because huge labor is demanded, and the work depends on editor's experiences and skills . Moreover, the accuracy of data would be lost during the editing works. In this research, using the laser profiler and a non-calibrated digital camera, a method is proposed for the automatic generation of 3D model by integrating these data. At first, region segmentation is applied to laser range data to extract geometric features of an object in the laser range data. Various information such as normal vectors of planes, distances from a sensor and a sun-direction are used in this processing. Next, an image segmentation is also applied to the digital camera images, which include the same object. Then, geometrical relations are determined by corresponding the features extracted in the laser range data and digital camera’ images. By projecting digital camera image onto the surface data reconstructed from laser range image, the 3D texture model was generated automatically.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.375-378
• /
• 1997

This research deals with a problem of reconstructing 3D surface structures from their 2D projections, which is an important research topic in computer vision. In order to provide robust reconstruction algorithm, that is reliable even in the presence of uncertainty in the range images, we first present a detailed model and analysis of several error sources and their effects on measuring three-dimensional surface properties using the space encoded range imaging technique. Our approach has two key elements. The first is the error modeling for the space encoding range sensor and its propagation to the 3D surface reconstruction problem. The second key element in our approach is the algorithm for removing outliers in the range image. Such analyses, to our knowledge, have never attempted before. Experimental results show that our approach is significantly reliable.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.31B no.2
• /
• pp.69-79
• /
• 1994

The conventional machine vision system which has uniform rectangular grid requires tremendous amount of computation for processing and analysing an image especially in 2-D image transfermations such as scaling, rotation and 3-D reconvery problem typical in robot application environment. In this study, the imaging system with nonuiformly distributed image sensors simulating human visual system, referred to as Ploar Exponential Grid(PEG), is compared with the existing conventional uniform rectangular grid system in terms of image resolution and computational complexity. By mimicking the geometric structure of the PEG sensor cell, we obtained PEG-like images using computer simulation. With the images obtained from the simulation, image resolution of the two systems are compared and some basic image processing tasks such as image scaling and rotation are implemented based on the PEG sensor system to examine its performance. Furthermore Fourier transform of PEG image is described and implemented in image analysis point of view. Also, the range and heading-angle measurement errors usually encountered in 3-D coordinates recovery with stereo camera system are claculated based on the PEG sensor system and compared with those obtained from the uniform rectangular grid system. In fact, the PEC imaging system not only reduces the computational requirements but also has scale and rotational invariance property in Fourier spectrum. Hence the PEG system has more suitable image coordinate system for image scaling, rotation, and image recognition problem. The range and heading-angle measurement errors with PEG system are less than those of uniform rectangular rectangular grid system in practical measurement range.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.31B no.7
• /
• pp.190-198
• /
• 1994

In this paper, we propose the cross-section processing method which is simple in describing the SHGC of objects in a range image and which can describe the SHGC of occluded objects for the recognition of 3D objects. This method produces the cross-sections of an object along the assumed axis of the SHGC and describes the SHGC of the object by processing the produced cross-sections of the object using $\psi$ -S curves with invariant properties in position and size. Our method is simple in a process and can descirbe the SHGC of partially occluded objects because it uses range images with 3-D informations of objects without matching contours of objects with a model base. Thus it is a useful description method of a range image for the recognition of 3D objects shaped in SHGC form and we proved the usefulness of it in experiments.