Range image denoising using a constrained local Gaussian model for 3D object query service in the smart space

A position and direction is a fundamental information for U-Business as an anywhere service. A mobile device camera image can increase an accuracy of the positioning, and a range image provides significant information in an occlusion scene. U-Business service queries the information with the range image for a precision position or a target object. We present a method for smoothing heavy noisy surfaces acquired by mobile 3D imaging devices to obtain the stable curvature. The smoothing is performed in a way that finds centers of probability distributions, which maximizes the likelihood of observed points with smooth constraints. The smooth constraints are derived from the unit tangent vector equality. This provides a way of obtaining smooth surfaces and stable curvatures. We achieve the smoothing by solving the regularized linear system. The unit tangent vector equality involves consideration of geometric symmetry, and it minimizes the variation of differential values that are a factor of curvatures. The proposed algorithm has two apparent advantages. The first thing is that the surfaces in a scene with various signals-to-noise ratio are smoothed, and then they can earn suitable curvatures. The second is that the proposed method works on heavy noisy surfaces, for example, a stereo camera image. Experiments on range images demonstrate that the proposed method yields the smooth surfaces from the input with various signals-to-noise ratio and the stable curvatures obtained from the smooth surfaces.     

Low level light therapy by Red–Green–Blue LEDs improves healing in an excision model of Sprague–Dawley rats

There are many methods of healing wounds. Among these, light therapy is reported to be beneficial, as beams assist the human body in treating, sterilizing, and regenerating cells. Both Laser and LED irradiation with specific wavelengths induce proliferation of fibroblasts depending on the wound area or wavelength and are effective in wound healing. This study used 8-week-old 250–300 g Male Sprague–Dawley Rats (ILAR Code: NTacSam:SD). The experiment was carried out for the non-irradiation group and the Red–Green–Blue LEDs irradiation groups (n of each group = 5). The experiment animals were relieved for 24 h after wounds had been excised and then the Red–Green–Blue LEDs irradiation groups were given irradiation therapy over 9 days 1 h per day. Immunohistochemical staining was conducted for cytokeratin in order to precisely measure the defect size. Also, Masson’s trichrome staining was conducted for comparison of collagen between the Red–Green–Blue LEDs irradiation groups and the non-irradiation group. Animals treated with Blue LEDs irradiation (p < 0.05), Green LEDs irradiation (p < 0.05), and Red LEDs irradiation (N.S.) healed at a faster rate than non-irradiated group. The LEDs irradiated groups also had more collagen, according to Masson’s trichrome staining for collagen analysis. The Red–Green–Blue LEDs irradiation had a beneficial effect on wound healing and could probably replace low power laser treatment.     

Collaborative assignment using belief-desire-intention agent modeling and negotiation with speedup strategies

In this paper, we propose a distributed agent model that applies belief-desire-intention (BDI) reasoning and negotiation for addressing the linear assignment problem (LAP) collaboratively. In resource allocation, LAP is viewed as seeking a concurrent allocation of one different resource for every task to optimize a linear sum objective function. The proposed model provides a basic agent-based foundation needed for efficient resource allocation in a distributed environment. A distributed agent algorithm that has been developed based on the BDI negotiation model is examined both analytically and experimentally. To improve performance in terms of average negotiation speed and solution quality, two initialization heuristics and two different reasoning control strategies are applied, with the latter yielding different variants of the basic algorithm. Extensive simulations suggest that all the heuristic-algorithm combinations can produce a near optimal solution soon enough in some specific sense. The significance and applicability of the research work are also discussed.     

Application of load balancing based on symmetric balanced incomplete block design to random networks

In a load balancing algorithm [O. Lee, M. Anshel, I. Chung, Design of an efficient load balancing algorithm on distributed networks by employing symmetric balanced incomplete block design, IEE Proceedings - Communications 151 (6) (2004) 535-538] based on the SBIBD (Symmetric Balanced Incomplete Block Design), each node receives global workload information by only two round message exchange with traffic overhead, where v is the number of nodes. It is very efficient and works well only when v=p²+p+1 is used for a prime number p. In this paper, we generated a special incidence structure using the SBIBD and then propose a new load balancing algorithm, which executes well for an arbitrary number of nodes. To accomplish this, we add a number of links to nodes in order for each node to receive more than 80% of the workload information by two round message exchange. For performance of our algorithm, we carried out an experiment for the number of nodes, w, which was up to 5000. Traffic overhead is less than in a round and standard deviation of traffic overhead shows that each node has a mostly well-balanced amount of traffic.     

Image retrieval model based on weighted visual features determined by relevance feedback

An accurate and rapid method is required to retrieve the overwhelming majority of digital images. To date, image retrieval methods include content-based retrieval and keyword-based retrieval, the former utilizing visual features such as color and brightness, and the latter utilizing keywords that describe the image. However, the effectiveness of these methods in providing the exact images the user wants has been under scrutiny. Hence, many researchers have been working on relevance feedback, a process in which responses from the user are given as feedback during the retrieval session in order to define a user’s need and provide an improved result. Methods that employ relevance feedback, however, do have drawbacks because several pieces of feedback are necessary to produce an appropriate result, and the feedback information cannot be reused. In this paper, a novel retrieval model is proposed, which annotates an image with keywords and modifies the confidence level of the keywords in response to the user’s feedback. In the proposed model, not only the images that have been given feedback, but also other images with visual features similar to the features used to distinguish the positive images are subjected to confidence modification. This allows for modification of a large number of images with relatively little feedback, ultimately leading to faster and more accurate retrieval results. An experiment was performed to verify the effectiveness of the proposed model, and the result demonstrated a rapid increase in recall and precision using the same amount of feedback.     

Color segmentation robust to brightness variations by using B-spline curve modeling

Color segmentation takes a great attention because color is an effective and robust visual cue for characterizing an object from the others. However, color segmentation suffers from color variations incurred by irregular illumination changes. We propose a reliable color modeling approach in hue–saturation–intensity (HSI) color space while considering intensity information by adopting the B-spline curve fitting to make a mathematical model for statistical characteristics of a color with respect to intensity. It is based on the fact that color distribution of a single-colored object is not invariant with respect to brightness variations even in the HS (hue–saturation) plane. The statistical characteristics contain the mean and standard deviation of hue and saturation with respect to intensity. They are mathematically expressed as four bar graphs. In order to fit the bar graphs to continuous curves, we use B-spline curve fitting procedure. From several experimental results, we verify that the proposed algorithm is successfully applied to color segmentation under various illumination conditions.     

Use of a dark object concept and support vector machines to automate forest cover change analysis

An automated method was developed for mapping forest cover change using satellite remote sensing data sets. This multi-temporal classification method consists of a training data automation (TDA) procedure and uses the advanced support vector machines (SVM) algorithm. The TDA procedure automatically generates training data using input satellite images and existing land cover products. The derived high quality training data allow the SVM to produce reliable forest cover change products. This approach was tested in 19 study areas selected from major forest biomes across the globe. In each area a forest cover change map was produced using a pair of Landsat images acquired around 1990 and 2000. High resolution IKONOS images and independently developed reference data sets were available for evaluating the derived change products in 7 of those areas. The overall accuracy values were over 90% for 5 areas, and were 89.4% and 89.6% for the remaining two areas. The user's and producer's accuracies of the forest loss class were over 80% for all 7 study areas, demonstrating that this method is especially effective for mapping major disturbances with low commission errors. IKONOS images were also available in the remaining 12 study areas but they were either located in non-forest areas or in forest areas that did not experience forest cover change between 1990 and 2000. For those areas the IKONOS images were used to assist visual interpretation of the Landsat images in assessing the derived change products. This visual assessment revealed that for most of those areas the derived change products likely were as reliable as those in the 7 areas where accuracy assessment was conducted. The results also suggest that images acquired during leaf-off seasons should not be used in forest cover change analysis in areas where deciduous forests exist. Being highly automatic and with demonstrated capability to produce reliable change products, the TDA-SVM method should be especially useful for quantifying forest cover change over large areas.     

Influence of wall charge distribution on time lag of address discharge in AC plasma display panels

The influence of wall charge distribution on the time lag of address discharge in an AC plasma display panel is investigated using two different reset waveforms: one (typical reset) induces both face and surface discharges and the other (TR reset) induces face discharges only. The measured formative time lag and statistical time lag of address discharge for TR were 21–31 ns and 31–74 ns shorter than the one for the typical reset, respectively. The TR reset resulted in much less increase of statistical time lag than the typical reset when the reset-to-address time interval was increased, and 70 ns smaller deviation of the statistical time lag among different color cells. Calculations show that the TR reset forms a much smoother wall charge profile, which is less susceptible to cell parameter variations, than the typical reset. The observed differences in the time lags of address discharge between different scan lines and color cells are strongly correlated to the differences of the wall charge profile, indicating that a smooth wall charge profile formed by the reset using face discharges only reduces the time lag of address discharge and minimizes the susceptibility of address discharge to cell parameter variation.     

Hermite interpolation with simple planar PH curves by speed reparametrization

We introduce a new method of solving C¹ Hermite interpolation problems, which makes it possible to use a wider range of PH curves with potentially better shapes. By characterizing PH curves by roots of their hodographs in the complex representation, we introduce PH curves of type K(t−c)²ⁿ⁺¹+d. Next, we introduce a speed reparametrization. Finally, we show that, for C¹ Hermite data, we can use PH curves of type K(t−c)²ⁿ⁺¹+d or strongly regular PH quintics satisfying the G¹ reduction of C¹ data, and use these curves to solve the original C¹ Hermite interpolation problem.     

Characterization for High Dynamic Range Imaging

In this paper we present a new practical camera characterization technique to improve color accuracy in high dynamic range (HDR) imaging. Camera characterization refers to the process of mapping device‐dependent signals, such as digital camera RAW images, into a well‐defined color space. This is a well‐understood process for low dynamic range (LDR) imaging and is part of most digital cameras — usually mapping from the raw camera signal to the sRGB or Adobe RGB color space. This paper presents an efficient and accurate characterization method for high dynamic range imaging that extends previous methods originally designed for LDR imaging. We demonstrate that our characterization method is very accurate even in unknown illumination conditions, effectively turning a digital camera into a measurement device that measures physically accurate radiance values — both in terms of luminance and color — rivaling more expensive measurement instruments.