LOCAL FEATURE EXTRACTION IN IMAGES

The methods of the local feature point extraction are analyzed. The analysis shows that the most effective detectors are based on the brightness gradient determination. They usually use the Harris angle detector, which is complex in calcu­la­tions. The algorithm complexity minimization contradicts both the detector effective­ness and to the high dynamic range of the analyzed image. As a result, the high-speed methods could not recognize the feature points in the heavy luminance conditions. The modification of the high dynamic range (HDR) image compression algorithm based on the Retinex method is proposed. It contains an adaptive filter, which preserves the image edges. The filter is based on a set of feature detectors perfor­ming the Harris-Laplace transform which is much simpler than the Harris angle detector. A prototype of the HDR video camera is designed which provides sharp images. Its structure simplifies the design of the artificial intelligence engine, which is implemented in FPGA of medium or large size.

Open Platform Cameras Based Bio-Imaging Evaluation System

With the active development of mobile devices, a variety of ultra-small, high-definition, and open platform-based cameras are being mass-produced. In this paper, we established an emulation system to verify the bio-imaging performance of the bulky and expensive high-performance cameras and various smartphone cameras that have been used in bio-imaging devices. In the proposed system, the linearity of the brightness gradient change of four types of cameras was compared and analyzed. Based on these results, three cameras were selected in order of excellent linearity, and gel image analysis results were compared.

Detecting the Dynamics of Urban Growth in Africa Using DMSP/OLS Nighttime Light Data

Africa has been experiencing a rapid urbanization process, which may lead to an increase in unsustainable land use and urban poverty. Assessing the spatiotemporal characteristics of urbanization dynamics is especially important and needed for the sustainable development of Africa. Satellite-based nighttime light (NTL) data are widely used to monitor the dynamics of urban growth from global to local scales. In this study, urban growth patterns across Africa were analyzed and discussed using stable nighttime light datasets obtained from DMSP/OLS (the Defense Meteorological Satellite Program’s Operational Line-scan System) spanning from 1992 to 2013. We partitioned the nighttime lighting areas into three types (low, medium, and high) using thresholds derived from the Brightness Gradient (BG) method. Our results indicated that built-up areas in Africa have increased rapidly, particularly those areas with low nighttime lighting types. Countries with higher urbanization levels in Africa, like South Africa, Algeria, Egypt, Nigeria, and Libya, were leading the brightening trend. The distribution of nighttime lighting types was consistent with the characteristics of urban development, with high nighttime lighting types showed up at the urban center, whereas medium and low nighttime lighting types appeared in the urban-rural transition zone and rural areas respectively. The impacts of these findings on the future of African cities will be further proposed.

The Dynamic Double Flash Illusion: Auditory Triggered Replay of Illusory Visual Expansion

In the original double flash illusion, a visual flash (e.g., a sharp-edged disk, or uniformly filled circle) presented with two short auditory tones (beeps) is often followed by an illusory flash. The illusory flash has been previously shown to be triggered by the second auditory beep. The current study extends the double flash illusion by showing that this paradigm can not only create the illusory repeat of an on-off flash, but also trigger an illusory expansion (and in some cases a subsequent contraction) that is induced by the flash of a circular brightness gradient (gradient disk) to replay as well. The perception of the dynamic double flash illusion further supports the interpretation of the illusory flash (in the double flash illusion) as similar in its spatial and temporal properties to the perception of the real visual flash, likely by replicating the neural processes underlying the illusory expansion of the real flash. We show further that if a gradient disk (generating an illusory expansion) and a sharp-edged disk are presented simultaneously side by side with two sequential beeps, often only one visual stimulus or the other will be perceived to double flash. This indicates selectivity in auditory–visual binding, suggesting the usefulness of this paradigm as a psychophysical tool for investigating crossmodal binding phenomena.

SEGMENTATION OF IMAGES OF EYE GROUND BLOOD VESSELS INVOLVING APPLICATION OF FUZZY IMAGING

Segmentation of images is an important task while processing images. Among the most widespread methods are methods based on pixel clustering, histogram methods, morphological methods, watershed segmentation, multiscale segmentation, and others. A promising trend in image processing is the use of fuzzy logic methods and the fuzzy set theory. Their application makes it possible to improve the quality of processing by providing information in a fuzzy form. The article proposes a new method for images segmentation involving boundaries detection based on the fuzzy representation of the image and fuzzy pixels. The membership functions are proposed for describing fuzzy pixels, and the requirements for their form and type are provided. The most suitable membership functions for fuzzy imaging are the s-function and the π-function. A description of a new method for boundaries detection based on the Sobel operator and the developed fuzzy type of image is described. In this case, standard calculations of the image brightness gradient are supplemented with their fuzzy versions which are then combined to obtain the final result. The experimental verification of the developed method is carried out using the example of eyeground images. In addition to the fuzzy detection of boundaries for the detection of blood vessels, the images were subjected to pre-processing (halftone imaging, mask matching, contrasting), morphological operators (thinning of boundaries, dilatation), and an algorithm for removing small details was applied. During testing, the developed algorithm showed acceptable results in terms of segmentation of blood vessels. In the future, a fuzzy image model can be extended to use fuzzy features of the second and higher types

Analyses of DNA Image Cytometry Uncertainty Caused by Diffractive Blurring

Comparison of quantitative methods for the segmentation of nuclei images is performed. A sizeable variability is typical for biological specimens and it induces the elemental uncertainty in experimental data. To remove the variability from comparison we have proposed and built the special test objects of two types simulating the nuclei images. I-type objects are test patterns as sets of circles and squares of specified dimensions in chromium films on a glass plate. II-type objects are images with brightness differentials that simulate diffractive blurring and are built up with MathCad programming environment. Test objects enable objective comparison of characteristics obtained in the course of their quantitative optical-and-structural analysis using various algorithms and programs. We found that the efficiency of the segmentation algorithm depends on diffractive blurring of the image. Specifics of Otsu’s algorithm and local algorithm of brightness gradient are analyzed for finding the segmentation threshold of digital images modeling transmission Feulgen-stained cell nuclei specimens with diffractive blurring. The performed calculations revealed that the border of geometrooptical image practically coincide with the points of inflection on the intensity distribution graph in a test-object image space. Computational experiments show that quantitative results of the morphometric image study defined by the various segmentation algorithms vary within 5%. It is established that the threshold-identifying algorithm based on the brightness gradient is preferable in the image cytometry.

Optical Flow and Prediction Residual Based Hybrid Forensic System for Inter-Frame Tampering Detection

In the wake of widespread proliferation of inexpensive and easy-to-use digital content editing software, digital videos have lost the idealized reputation they once held as universal, objective and infallible evidence of occurrence of events. The pliability of digital content and its innate vulnerability to unobtrusive alterations causes us to become skeptical of its validity. However, in spite of the fact that digital videos may not always present a truthful picture of reality, their usefulness in today’s world is incontrovertible. Therefore, the need to verify the integrity and authenticity of the contents of a digital video becomes paramount, especially in critical scenarios such as defense planning and legal trials where reliance on untrustworthy evidence could have grievous ramifications. Inter-frame tampering, which involves insertion/removal/replication of sets of frames into/from/within a video sequence, is among the most un-convoluted and elusive video forgeries. In this paper, we propose a potent hybrid forensic system that detects inter-frame forgeries in compressed videos. The system encompasses two forensic techniques. The first is a novel optical flow analysis based frame-insertion and removal detection procedure, where we focus on the brightness gradient component of optical flow and detect irregularities caused therein by post-production frame-tampering. The second component is a prediction residual examination based scheme that expedites detection and localization of replicated frames in video sequences. Subjective and quantitative results of comprehensive tests on an elaborate dataset under diverse experimental set-ups substantiate the effectuality and robustness of the proposed system.