Division of images into areas of local extrema with a monotonic change in pixel brightness

In this paper, the problem of segmentation of halftone images is considered, in which areas of local maxima and minima (extrema) are distinguished with a monotonic change in the brightness of pixels from local extrema to the boundaries of areas. To solve this problem, a mathematical model is proposed and a segmentation algorithm is developed on the basis of counter-wave growing of local extremum regions. The developed algorithm differs from the known segmentation algorithms by using a set of brightness thresholds (by the number of regions), varying by one in each cycle, starting from the values of local extrema, taking into account the increase or decrease in brightness to select adjacent pixels that are attached to the regions formed from these local extrema. The algorithm provides a greater deviation of pixel brightness from the average value within the region compared to known segmentation algorithms. This does not allow evaluating its efficiency using known indicators based on the variance of the brightness within the region. In this regard, estimates of the monotonicity of changes in the brightness of regions are proposed based on a) the shortest distances from each pixel of the region to the corresponding local extremum along the routes determined by the maximum increase (for the region of the local maximum) or decrease (for the region of the local minimum) the brightness of pixels and b) taking into account the number pixels that break the monotony of the segment brightness change. Using these estimates, it is shown that the proposed algorithm provides segmentation of artificial and natural grayscale images with a monotonic change in the brightness of pixels in the areas of local extrema. These properties allow us to consider the developed algorithm as a basis for the selection of texels, spots, low-contrast objects in images.

Albedo and Thermal Ecology of White, Red, and Black Cows (Bos taurus) in a Cold Rangeland Environment

Cattle in high-elevation rangelands experience cold and hot extremes. Given the increase in black hided cattle globally, thermoregulation options on rangelands, and hide color function affecting mammal thermal ecology, this study quantified winter albedo, external cattle temperatures (Tempcow), and differences (ΔT) between Tempcow and ambient air temperature (Tempamb), for different color cattle along a thermal gradient (≈−33 °C to +33 °C). From 2016 to 2018, I measured 638 individual Tempcow × Tempamb combinations for white (n = 183), red (n = 158), and black (n = 297) Bos taurus female cattle free roaming extensive Wyoming, USA rangelands. Pixel brightness of cow images relative to snow indicated mean (±standard error) albedo for white, red, and black cows (n = 3 of each) was 0.69 (±0.15), 0.16 (±0.04), and 0.04 (±0.01), respectively (p = 0.0027). Tempcow was explained by Tempamb (+), clear sky insolation index (+), and cow albedo (−). However, ΔT was explained by Tempamb (−), long-wave radiation (infrared; RadLW (−)), Tempcow (+), and cow albedo (+). Tempamb relative to ΔT was correlated for all hide colors (all p-values < 0.0001; all r2 values > 0.7)), yet slopes (m) were ~2× greater for red and black cows than white cows.

The Use of Bone Fluorescence to Facilitate DNA Sampling

DNA is increasingly used in skeletal remains cases for identification and to resolve commingling. The implementation of a sampling strategy based on the likelihood of obtaining viable DNA profiles could minimize destruction of bones, expedite identification, and save time and resources by reducing the need to resample. Here we test whether bone fluorescence is a good indicator of potential DNA yield. Samples consisted of remains from seven different burial sites analyzed by the Committee on Missing Persons in Cyprus Anthropological Laboratory that were submitted for DNA analysis to an external DNA laboratory. Fluorescence was assessed as a function of pixel brightness values using images of bone and tooth samples captured using an alternate light source and measured in ImageJ. Across seven pooled sites, no relationship was apparent between fluorescence and DNA extracted, but there was a positive relationship when certain sites were considered in isolation. These results appear to suggest no overall relationship between fluorescence and DNA extracted; however, given the mixed nature of these results, additional research using a more controlled sample is needed.

Projection-mapping-based object pointing using a high-frame-rate camera-projector system

The novel approach to physical security based on visible light communication (VLC) using an informative object-pointing and simultaneous recognition by high-framerate (HFR) vision systems is presented in this study. In the proposed approach, a convolutional neural network (CNN) based object detection method is used to detect the environmental objects that assist a spatiotemporal-modulated-pattern (SMP) based imperceptible projection mapping for pointing the desired objects. The distantly located HFR vision systems that operate at hundreds of frames per second (fps) can recognize and localize the pointed objects in real-time. The prototype of an artificial intelligence-enabled camera-projector (AiCP) system is used as a transmitter that detects the multiple objects in real-time at 30 fps and simultaneously projects the detection results by means of the encoded-480-Hz-SMP masks on to the objects. The multiple 480-fps HFR vision systems as receivers can recognize the pointed objects by decoding pixel-brightness variations in HFR sequences without any camera calibration or complex recognition methods. Several experiments were conducted to demonstrate our proposed method’s usefulness using miniature and real-world objects under various conditions.

Projection-Mapping-Based Object Pointing Using a High-Frame-Rate Camera-Projector System

The novel approach to physical security based on visible light communication (VLC) using an informative object-pointing and simultaneous recognition by high-framerate (HFR) vision systems is presented in this study. In the proposed approach, a convolutional neural network (CNN) based object detection method is used to detect the environmental objects that assist a spatiotemporal-modulated-pattern (SMP) based imperceptible projection mapping for pointing the desired objects. The distantly located HFR vision systems that operate at hundreds of frames per second (fps) can recognize and localize the pointed objects in real-time. The prototype of an artificial intelligence-enabled camera-projector (AiCP) system is used as a transmitter that detects the multiple objects in real-time at 30~fps and simultaneously projects the detection results by means of the encoded-480-Hz-SMP masks on to the objects. The multiple 480-fps HFR vision systems as receivers can recognize the pointed objects by decoding pixel-brightness variations in HFR sequences without any camera calibration or complex recognition methods. Several experiments were conducted to demonstrate our proposed method's usefulness using miniature and real-world objects under various conditions

Vector fields created by Fourier transform of video signals

The power spectrum and autocorrelation are widely used in video signals processing. The phase-frequency spectrum contains more information than the amplitude spectrum. However, the amplitude spectrum is used more often in the video signal process. It is possible to combine the advantages of these two spectra to obtain a vector function such as phase-energy spectrum. This spectrum is sensitive even to a small difference in pixel brightness but at the same time it is as stable as the power spectrum. In this paper, we explored the properties of the phase-power spectrum and related amplitude of partials vector field. We showed that phase-power spectrum has conservative as well as solenoidal components and so it creates curl’s vector field. We also found the components of phase-power spectra that contain pixels with a different degree of contrast on the uniform background. We showed the possibility to use solenoidal component of the phase-power vector field to find the circulation (i.e. field work). We concluded that the circulation along any of brightness contour constants, which is symmetrical to the origin, is equal zero. We explored two-dimensional vector field of the phase-power spectrum. Finally, we determined an effect of pixels with different degree of brightness and their relative position to the image’s edges on vector field’s components formation.

Estimation of Optimal Number of Rays in the Bidirectional Photon Mapping Method

The classic Monte-Carlo ray tracing is a powerful technique for simulating almost all effects in ray optics, but it may be prohibitively slow for, for example, calculation of images seen by a lens camera. Therefore, in practice there are often used its various modifications, in particular, bi-directional stochastic ray tracing with photon maps. The well-known flaw of all stochastic methods is their noise. The noise level, that is, the root mean square of pixel brightness calculated during given time, depends, besides all, on the number of rays traced from the light source and from the camera. The choice of the optimal parameters must provide the lowest noise level in a fixed time. This article is devoted to the choice of the optimal number of rays that minimizes the noise. It is proved that this minimal noise is in the same time homogeneous over the image. We produce the formulae to calculate the optimal number of rays from several coefficients which can be obtained from a bi-directional ray tracing of several auxiliary variants. It happens that this optimum is rather wide i.e. the noise level changes with the number of rays slowly, which allows to choose it including other factors e.g. limit this number to save memory.

BRIGHTNESS-CONTRAST MAGNIFIER ALGORITHM AND METHODS OF ITS ENHANCING

The paper considers the algorithmic basis of the developed application, which allows the user to select image fragments for viewing not only in enlarged form, but also with increased detail distinctness through brightness-contrast transformations. There has been proposed an algorithm of upsizing and processing the selected image fragment according to the required parameters of average brightness and contrast. The advantages of the proposed method of image processing in comparison with global methods for processing the entire image are investigated. The considered approach develops the advantages when marking low-contrast fragments that are close to monotone in images with fragments of different brightness. The experiments on processing various fragments of images were carried out using a specially developed program. The examples of results have been presented. The behavior of two types of fragments on simplified models of pixel brightness distribution has been analyzed, and for this reason there was made a conclusion about further improving the approach.