Laser range scanner based on self-calibration techniques using coplanarities and metric constraints

In this paper, we propose a novel method to achieve both dense 3D reconstruction of the scene and estimation of the camera intrinsic parameters by using coplanarities and other constraints (e.g., orthogonalities or parallelisms) derived from relations between planes in the scene and reflected curves of line lasers captured by a single camera. In our study, we categorize coplanarities in the scene into two types: implicit coplanarities, which can be observed as reflected curves of line lasers, and explicit coplanarities, which are, for example, observed as walls of a building. By using both types of coplanarities, we can construct simultaneous equations and can solve them up to four degrees of freedom. To upgrade the solution to the Euclidean space and estimate the camera intrinsic parameters, we can use metric constraints such as orthogonalities of the planes. Such metric constraints are given by, for example, observing the corners of rectangular boxes in the scene, or using special laser projecting device composed of two line lasers whose laser planes are configured to be perpendicular.     

Generating function of color information detection using genetic programming

This article proposes a function for color information detection using genetic programming (GP). In image-processing, object detection is one of the important processes. In cases where the object has a complex color domain, detection becomes more difficult. We generated a detection function for a complex color domain by using GP. The detection function deals with one pixel of an input image, and it obtains an output image by processing for all pixels. We aimed at a reduction in the time taken by a human to consider an image-processing system design. We applied the generation of GP to detect a target color region in actual images. The results show that the detection function has sufficient ability for these detections.     

Using formal methods to increase confidence in a home network system implementation: a case study

A home network system consists of multiple networked appliances, intended to provide more convenient and comfortable living for home users. Before being deployed, one has to guarantee the correctness, the safety, and the security of the system. Here, we present the approach chosen to validate the Java implementation of a home network system. We rely on the Java Modelling Language to formally specify and validate an abstraction of the system. This is a substantially revised version of our paper that appeared in the proceedings of the Workshop On Leveraging Applications of Formal Methods, Verification and Validation (ISoLA), Poitiers-Futuroscope, France, December 2007.     

A novel method for three-dimensional observation of the vascular networks in the whole mouse brain

A novel method for acquiring serial images suitable for three-dimensional reconstruction of vascular networks in the whole brain of mouse was developed. The brain infused with a White India ink-gelatin solution was fixed and embedded in paraffin containing Sudan Black B through xylene also containing Sudan Black B. Each sliced surface of the paraffin block was coated with liquid paraffin and its image was serially acquired. Coating with liquid paraffin extremely improved the quality of the image. The series of serial images was free of distortion and a three-dimensional image was reconstructed without the problem of the alignment and registration of adjacent images. The volume-rendered image indicated three-dimensional distribution of blood vessels in a whole brain. No ghost or shadow was observed on a volume-rendered image of the White India ink-gelatin infused brain. The z-axial resolution examined on the orthogonal sections reconstituted from serial images obtained at an interval of 5 mum showed no cross talk, indicating that the z-axial resolution was no larger than 5 mum. A proper understanding of the vascular system in a whole brain is indispensable to reveal the development of the vascular system in the brain of normal and genetically manipulated mouse and vascular alterations in pathological situation, such as stroke and neurodegenerative disease. Although simple and inexpensive, this method will provide fundamental information on the vascular system in a whole brain.     

Threshold for Millimeter-Wave (60 GHz)-Induced Ocular Injury

Journal of Infrared, Millimeter, and Terahertz Waves - Millimeter waves (MMW) absorbed by skin or cornea may induce damage by heat. We have developed a 60 GHz MMW exposure-induced eye...     

Fractal analysis of the surface cracks on continuously cast steel slabs

Data concerning the length of longitudinal cracks on the surface of continuously cast steel slabs were collected from two plants. The data were analyzed to find the relation between crack length and crack frequency. The analysis revealed the following.

Studies of 2D Cryocrystals by STM Techniques

Scanning tunneling microscopy (STM) studies of two-dimensional (2D) cryocrystals ⁴ He, Kr, Xe) physisorbed on graphite surfaces are presented. Individual helium atoms, usually thought to be invisible with STM, were recently observed on graphite surfaces at a density corresponding to the commensurate solid. Here we show that a local elastic deformation seems to be the principal mechanism responsible to render the atoms visible. Recent tight-binding calculations of the local density of states (LDOS) of graphite which predict the appearance of an energy gap support this picture. I-z curve measurements for the case of ⁴ He show a sharp drop (increase) of the tunneling current I at a certain tip-surface distance z during retraction (approach) of the tip. This drop (increase) may be associated with the tunneling of a single He adatom, opening new possibilities to study the quantum tunneling of atoms via STM.     

A Hilbert warping method for handwriting gesture recognition

We propose a novel sequence alignment algorithm for recognizing handwriting gestures by a camera. In the proposed method, an input image sequence is aligned to the reference sequences by phase-synchronization of analytic signals which are transformed from original feature values. A cumulative distance is calculated simultaneously with the alignment process, and then used for the classification. A major benefit of this method is that over-fitting to sequences of incorrect categories is restricted. The proposed method exhibited higher recognition accuracy in handwriting gesture recognition, compared with the conventional dynamic time warping method which explores optimal alignment results for all categories.