Dynamic Thresholding Technique Research Articles

Selection of optimal SINR threshold in fractional frequency reuse by comparing Otsu's and entropy method

Interference is a major challenge in cellular networks and has been mitigated by introducing a frequency re-use factor to alternate the frequency used by adjacent cells. Fractional Frequency Re-use is an approach that is utilized in handling interferences which occur between cells, particularly in cellular networks using long-term evolution and leads to better bandwidth utilization. The basic cell structure is split into two regions, a partial re-use region and a full re-use region. The full re-use region uses the same frequency for all the cells while the partial re-use regions adopt a re-use factor to mitigate interference with neighboring cells. The Signal-to-Interference-plus-Noise-Ratio threshold is a vital parameter to be set in Fractional Frequency re-use since it sets the basis of determining the subscribers that will fall within the full re-use region and those that will fall in the partial re-use region. The bandwidth is then allocated proportionately based on the number of subscribers in respective regions using a frequency partitioning ratio. The focus of this paper develop a dynamic thresholding technique by testing the performance of two thresholding techniques which are mostly used in image processing and include Otsu's, and entropy methods The results are validated by comparing the performance metrics of throughput and fairness with a dynamic thresholding technique from literature called centralized dynamic frequency allocation technique. The cell Signal-to-Interference-plus-Noise-Ratio value obtained from subscribers in the network are used to set threshold which is periodically updated as the subscribers continuously report their signal values. Simulation results show that Otsu's method outperforms entropy method in terms of throughput averagely by 29% and 23.3% in terms of fairness. Otsu outperforms centralized dynamic frequency allocation technique averagely by 39% in throughput and 32.9% in fairness.

Investigating the environmental impacts of coal mining using remote sensing and in situ measurements in Ruqigou Coalfield, China.

China is the largest producer and consumer of coal in the world. The extraction of coal is increasing intensively to meet the needs of the ever-increasing population and industries. However, coal mining has resulted in environmental changes, including deforestation, air, water, soil, and landform deterioration. This study investigates the impact of mining on the environment in Ruqigou coalfield by utilising in situ and remote sensing data. Field data collected include temperature, gas compositions, and water samples. Multi-temporal Landsat data of 1991, 2003, and 2019 were used in monitoring the impact of mining on different land covers, especially vegetation. A supervised classification was performed to assess the changes in land cover. In order to track the changes in vegetation, normalised difference vegetation index (NDVI) was employed. To study the changes in coal fire areas, thermal anomalies were extracted from the thermal infrared data using a dynamic thresholding technique. The results of in situ analyses show that water quality is unfit for domestic, industrial, and agricultural use. All the gas sampling sites emit noxious gases such as CO2, CO, NO2 and degrade the local air quality. The classified maps and vegetation indices show a significant decrease in vegetation. The thermal anomalies show an increase in fire areas over the years. Thus, it could be concluded that the conjunctive use of field-based measurements and remote sensing data can be a powerful tool for gaining a comprehensive understanding of the environmental impacts associated with large-scale mining.

Proper orthogonal decomposition of ice velocity identifies drivers of flow variability at Sermeq Kujalleq (Jakobshavn Isbræ)

Abstract. The increasing volume and spatio-temporal resolution of satellite-derived ice velocity data have created new exploratory opportunities for the quantitative analysis of glacier dynamics. One potential technique, proper orthogonal decomposition (POD), also known as empirical orthogonal functions, has proven to be a powerful and flexible technique for revealing coherent structures in a wide variety of environmental flows. In this study we investigate the applicability of POD to an openly available TanDEM-X/TerraSAR-X-derived ice velocity dataset from Sermeq Kujalleq (Jakobshavn Isbræ), Greenland. We find three dominant modes with annual periodicity that we argue are explained by glaciological processes. The primary dominant mode is interpreted as relating to the stress reconfiguration at the glacier terminus, known to be an important control on the glacier's dynamics. The second and third largest modes together relate to the development of the spatially heterogenous glacier hydrological system and are primarily driven by the pressurisation and efficiency of the subglacial hydrological system. During the melt season, variations in the velocity shown in these two subsidiary modes are explained by the drainage of nearby supraglacial melt ponds, as identified with a Google Earth Engine Moderate Resolution Imaging Spectroradiometer (MODIS) dynamic thresholding technique. By isolating statistical structures within velocity datasets and through their comparison to glaciological theory and complementary datasets, POD indicates which glaciological processes are responsible for the changing bulk velocity signal, as observed from space. With the proliferation of optical- and radar-derived velocity products (e.g. MEaSUREs, ESA CCI, PROMICE), we suggest POD, and potentially other modal decomposition techniques, will become increasingly useful in future studies of ice dynamics.

Fast Detection of Ground Plane in Stereo Vision Systems Based on Iso-Disparity Strip Pattern

In this paper, first a closed-form formulation is analytically derived for the pattern of iso-disparity strip widths associated with the ground plane in disparity map images. This formulation calculates the iso-disparity strip widths based on the parameters of the stereo camera setup ( i.e. , height, tilt angle, and baseline of the cameras) used to capture the images. The proposed formulation was then statistically validated using the results achieved in the case of a bank of stereo image pairs with different stereo camera setup parameters. Validation of the proposed formulation was in the presence of the strip width imperfections that appear in reality, and were shown to be in the form of additive Gaussian noise. Using the formulation proposed for iso-disparity strip widths, the paper then introduces a novel approach for ground plane detection based on the concept of iso-disparity strips in disparity map images. To add to the robustness of the proposed procedure against strip width noise, Cumulative Moving Average (CMA) and a dynamic thresholding technique are used to find the width of the strips corresponding to the ground plane. According to experimental results for synthesized and captured datasets, while exhibiting sufficiently low false positive rates (1.38% and 5.83%), the proposed method detects the ground plane with average true positive rates of as high as 80% and 54% in 65 ms and 224 ms, respectively.

Mobile Hardware Based Implementation of a Novel, Efficient, Fuzzy Logic Inspired Edge Detection Technique for Analysis of Malaria Infected Microscopic Thin Blood Images

This paper proposes a novel, efficient, low complexity algorithm for edge detection, with a cheap, easily accessible, networkable hardware implementation, specifically focused on the analysis of malaria infected thin blood smears. The algorithm presents a new and dynamic thresholding technique that eliminates inter-cell interference based on histogram analysis. Following this, binary image morphological processing is performed which is shown to outperform the same operation on the much more complex greyscale images. Edge tracking is done via a simplified fuzzy logic inspired rule system. The entire system is implemented on multiple platforms to test widespread compatibility but primarily developed for a battery powered standalone raspberry pi with low power, low resolution touchscreen and hardware buttons. The entire algorithm was pitted against the much more complex but still very well performing Canny algorithm, which despite the age, is still one of the most comprehensive edge detection techniques available; modern variants were considered and reviewed, but ultimately given the level of outperformance, they were not viable options.

A Dynamic Thresholding Technique In Spatially Co-Located Objects Mining From Vehicle Moving Data

Co-location pattern discovery is intended towards the processing data with spatial contexts to discover classes of spatial objects that are frequently located together. The existing moving vehicle location prediction technique not analyses the moving vehicles co-location instance. So, we improve the previous technique process by mining spatially co-located moving objects using spatial data mining techniques. Initially, the neighbour relationship is computed by the prim's algorithm. After that, the candidate co-locations are pruned according to the presence of candidate co-location in the input data and the final stage of co-location instances selection is performed by compute neighbourhood and node membership functions. The values obtained using neighbourhood membership function is compared with the dynamic threshold values. The co-location instances are selected which satisfy the dynamic threshold value. Moreover, the proposed co-location pattern mining with dynamic thresholding technique is compared with the existing co-location pattern mining technique.

A dynamic thresholding technique in spatially co-located objects mining from vehicle moving data

A dynamic thresholding technique in spatially co-located objects mining from vehicle moving data

Binary Features of Speech Signal for Recognition

Speech feature extraction is the mathematical representation of the speech file, which converts the speech waveform to some type of parametric representation for further analysis and processing in speech recognition. A good feature may produce a good result for any recognition system. This paper presents a simple and novel feature extraction approach for extracting binary features of Bangla speech words. This technique is based on frequency-domain signal features and dynamic thresholding method. First the frequency-domain signal feature, i.e., spectrogram feature is computed from the original speech words and then the binary features of these speech words are computed by using the dynamic thresholding technique. The developed system has been justified with several Bangla speech words. To test and analyse theses binary features, a speech recognition module has been developed. The speech recognition is done by using the neural network with back-propagation training algorithm. All the algorithms used in this research are implemented in MATLAB and the implemented speech recognition system achieved recognition accuracy of 96%.

A dynamic thresholding technique for extracting the automotive spark-ignition direct-injection pulsing spray characteristics

The macroscopic characteristics of fuel injection spray are crucial for spark-ignition direct-injection (SIDI) engines. To precisely quantify the macroscopic spray characteristics such as spray penetration length and spray angle, it is essential to determine the boundary of the spray structure from the images. Thresholding method is widely used for the spray boundary detection. It is normally achieved by selecting a single global thresholding value to distinguish the spray boundary from the image background. In this paper, a novel technique of dynamic thresholding, in which the threshold value is dynamically determined by the image local pixel intensity property in the vicinity of the spray boundary, is proposed. To evaluate the accuracy of the technique, a symmetric spray with well-defined geometry was used. The dynamic threshold method effectively reduced the difference between the right and left half-angles of the spray to only 0.5°, which is much smaller than the difference of as large as 3–4° obtained using global thresholding method. Similar results have been obtained for the spray penetration length measurements. Therefore, the proposed thresholding algorithm provides more accurate evaluation of macroscopic spray characteristics than the single-value global thresholding technique.

Detection of Coal Fire Dynamics and Propagation Direction from Multi-Temporal Nighttime Landsat SWIR and TIR Data: A Case Study on the Rujigou Coalfield, Northwest (NW) China

Coal fires are common and serious phenomena in most coal-producing countries in the world. Coal fires not only burn valuable non-renewable coal reserves but also severely affect the local and global environment. The Rujigou coalfield in Shizuishan City, Ningxia, NW China, is well known for being a storehouse of anthracite coal. This coalfield is also known for having more coal fires than most other coalfields in China. In this study, an attempt was made to study the dynamics of coal fires in the Rujigou coalfield, from 2001 to 2007, using multi-temporal nighttime Landsat data. The multi-temporal nighttime short wave infrared (SWIR) data sets based on a fixed thresholding technique were used to detect and monitor the surface coal fires and the nighttime enhanced thematic mapper (ETM+) thermal infrared (TIR) data sets, based on a dynamic thresholding technique, were used to identify the thermal anomalies related to subsurface coal fires. By validating the coal fires identified in the nighttime satellite data and the coal fires extracted from daytime satellite data with the coal fire map (CFM) manufactured by field survey, we found that the results from the daytime satellite data had higher omission and commission errors than the results from the nighttime satellite data. Then, two aspects of coal fire dynamics were analyzed: first, a quantitative analysis of the spatial changes in the extent of coal fires was conducted and the results showed that, from 2001 to 2007, the spatial extent of coal fires increased greatly to an annual average area of 0.167 km2; second, the spreading direction and propagation of coal fires was analyzed and predicted from 2001 to 2007, and these results showed that the coal fires generally spread towards the north or northeast, but also spread in some places toward the east.

Guided Autowave Pulse Coupled Neural Network (GAPCNN) based real time path planning and an obstacle avoidance scheme for mobile robots

Real time path planning for mobile robots requires fast convergence to optimal paths. Most rapid collision free path planning algorithms do not guarantee the optimality of the path. In this paper we present a Guided Autowave Pulse Coupled Neural Network (GAPCNN) approach for mobile robot path planning. The proposed model is a novel approach that improves upon the recently presented Modified PCNN (MPCNN) by introducing directional autowave control and accelerated firing of neurons based on a dynamic thresholding technique. Simulation studies and experimental results in both static as well as dynamic environments confirm GAPCNN to be a robust and time efficient path planning scheme for finding optimal paths.

Real-time skin color detection under rapidly changing illumination conditions

Skin color provides a useful cue for vision based human-computer interaction (HCI). However, rapidly changing illumination conditions under HCI application environment make skin color detection a challenging task, as skin colors in an image highly depend on the illumination under which the image was taken. This paper presents a method for skin color detection under rapidly changing illumination conditions. Skin colors are modeled under the Bayesian decision framework. Face detection is employed to online sample skin colors and a dynamic thresholding technique is used to update the skin color model. When there is no face detected, color correction strategy is employed to convert the colors of the current frame to those as they appear under the same illuminant of the last model updated frame. Skin color detection is then applied on the color corrected image. Face detection is time-consuming and hence should not be applied to every frame in real-time applications on general consumer hardware. To improve efficiency, a novel method is proposed to detect illumination changes, and face detection is used to update the skin color model only if the illumination has changed. Experimental results show that the proposed method can achieve satisfactory performance for skin color detection under rapidly changing illumination conditions in real-time on general consumer hardware.

DYNAMIC SEGMENTATION FOR AUTOMATIC SPRAY DEPOSITS ANALYSIS ON UNEVEN LEAF SURFACES

Four dynamic thresholding algorithms were implemented and evaluated to segment the images of spray depositson leaf surfaces. The algorithms were evaluated for accuracy to effectively segment the images that had nonuniform contrastbetween the droplets and the leaf background, and with varying intensities of the fluorescent tracer over uneven leaf surfaces.The analysis included segmentation of the droplets, estimation of droplet area, and the total number of different size and shapedroplet deposits on a leaf surface. Criteria were established to control the morphological operations during the imagesegmentation process. Guidelines for selecting a suitable dynamic thresholding technique for given image characteristics areproposed. A twopass approach was evaluated wherein the images were first thresholded by the best generalpurposetechnique to compute the blob characteristics, based on which an imagespecific thresholding algorithm was applied as thesecond pass for improved accuracy. The experimental results that are provided in this article reveal that this technique is veryeffective in segmenting images with nonuniform contrasts and could reduce the time required to characterize the spraydeposits.

Elimination of False-positive Candidates by Dynamic Thresholding Technique in an Automated Detection of Clustered Microcalcifications

Elimination of False-positive Candidates by Dynamic Thresholding Technique in an Automated Detection of Clustered Microcalcifications

External marker-based automatic congruencing: a new method of 3D reconstruction from serial sections.

Computer-based three-dimensional (3D) visualizations reconstructed from sectional images represent a valuable tool in biomedical research and medical diagnosis. Particularly with those imaging techniques that provide virtual sections, such as CT, MRI, and CLSM, 3D reconstructions have become routine. Reconstructions from physical sections, such as those used in histological preparations, have not experienced an equivalent breakthrough, due to inherent shortcomings in sectional preparation that impede automated image-processing and reconstruction. The increased use of molecular techniques in morphological research, however, generates an overwhelming amount of 3D molecular information, stored within series of physical sections. This valuable information can be fully appreciated and interpreted only through an adequate method of 3D visualization. In this paper we present a new method for a reliable and largely automated 3D reconstruction from physically sectioned material. The 'EMAC' concept (External Marker-based Automatic Congruencing) successfully approaches the three major obstacles to automated 3D reconstruction from serial physical sections: misalignment, distortion, and staining variation. It utilizes the objectivity of external markers for realignment of the sectional images and for geometric correction of distortion. A self-adapting dynamic thresholding technique compensates for artifactual staining variation and automatically selects the desired object contours. Implemented on a low-cost hardware platform, EMAC provides a fast and efficient tool that largely facilitates the use of computer-based 3D visualization for the analysis of complex structural, molecular, and genetic information in morphological research. Due to its conceptual versatility, EMAC can be easily adapted for a broad range of tasks, including all modern molecular-staining techniques, such as immunohistochemistry and in situ hybridization.

External marker‐based automatic congruencing: A new method of 3D reconstruction from serial sections

Background Computer-based three-dimensional (3D) visualizations reconstructed from sectional images represent a valuable tool in biomedical research and medical diagnosis. Particularly with those imaging techniques that provide virtual sections, such as CT, MRI, and CLSM, 3D reconstructions have become routine. Reconstructions from physical sections, such as those used in histological preparations, have not experienced an equivalent breakthrough, due to inherent shortcomings in sectional preparation that impede automated image-processing and reconstruction. The increased use of molecular techniques in morphological research, however, generates an overwhelming amount of 3D molecular information, stored within series of physical sections. This valuable information can be fully appreciated and interpreted only through an adequate method of 3D visualization. Methods and results:In this paper we present a new method for a reliable and largely automated 3D reconstruction from physically sectioned material. The ‘EMAC‘ concept (External Marker-based Automatic Congruencing) successfully approaches the three major obstacles to automated 3D reconstruction from serial physical sections: misalignment, distortion, and staining variation. It utilizes the objectivity of external markers for realignment of the sectional images and for geometric correction of distortion. A self-adapting dynamic thresholding technique compensates for artifactual staining variation and automatically selects the desired object contours. Conclusions Implemented on a low-cost hardware platform, EMAC provides a fast and efficient tool that largely facilitates the use of computer-based 3D visualization for the analysis of complex structural, molecular, and genetic information in morphological research. Due to its conceptual versatility, EMAC can be easily adapted for a broad range of tasks, including all modern molecular-staining techniques, such as immunohistochemistry and in situ hybridization. Anat. Rec. 248:583-602, 1997. © 1997 Wiley-Liss, Inc.

Fusion of satellite active and passive microwave data for sea ice type concentration estimates

Young first-year sea ice is nearly as important as open water in modulating heat flux between the ocean and atmosphere in the Arctic. Just after the onset of freeze-up, first-year ice is in the early stages of growth and will consist of young first-year and thin ice. The distribution of sea ice in this thickness range impacts heat transfer in the Arctic. Therefore, improving the estimates of ice concentrations in this thickness range is significant. The NASA Team Algorithm (NTA) for passive microwave data inaccurately classifies sea ice during the melt and freeze-up seasons because it misclassifies multiyear ice as first-year ice. We developed a hybrid fusion technique for incorporating multiyear ice information derived from synthetic aperture radar (SAR) images into a passive microwave algorithm to improve ice type concentration estimates. First, we classified SAR images using a dynamic thresholding technique and estimated the multiyear ice concentration. Then we used the SAR-derived multiyear ice concentration to constrain the NTA and obtained an improved first-year ice concentration estimate. We computed multiyear and first-year ice concentration estimates over a region in the eastern-central Arctic in which field observations of ice and in situ radar backscatter measurements were performed. The fused estimates of first-year and multiyear ice concentration appear to be more accurate than NTA, based on ice observations that were logged aboard the US Coast Guard Icebreaker Polar Star in the study area during 1991.

Progressive image transmission by dynamic binary thresholding

A new progressive image transmission scheme in the spatial domain is developed. The proposed scheme is demonstrated to be applicable to many interactive image communications. The progressive transmission of images could solve the problems related to the lengthy time required to transmit high-resolution images over low-speed channels. The proposed scheme is required to be computationally simple but result in a bit rate improvement. This technique is also demonstrated to be capable of developing operators such as a selective fill-in function. This scheme has encoded an approximate binary image, initially using context-free encoding. The approximate binary image is represented by two lists of identical elements maintained by both sides of the communication, with each list recording the locations of regions of homogeneous intensity. The dynamic thresholding technique is then applied to progressively refine the image. The dynamic threshold is defined as the mean of intensities for each stage. The original list is partitioned by the thresholdings. The information required for updating the lists is compressed by both the prefix coding and the runlength coding. An image can be progressively refined in the future because both sides of the communication maintain the locational lists of the same content. Several computer simulations using the proposed scheme and the bit-plane method are used to illustrate the advantages of the proposed scheme, which is confirmed by performance comparisons to obtain a better result than the bit-plane method.

An efficient evaluation of atomic properties using a vectorized numerical integration with dynamic thresholding

A new efficient algorithm for the evaluation of atomic properties by means of numerical integration over atomic basins is described. The fully vectorized algorithm takes advantage of a dynamic thresholding technique which neglects the primitive Cartesian Gaussian functions that do not contribute significantly to the properties of a given atom. This results in a procedure with a computational effort that scales only linearly with the size of the molecule in question, as opposed to the quadratic size dependence of the traditional approach. The ensuing savings in CPU time, which vary between 90% and 99%, make the determination of the properties of atoms in such molecules as C 60 and C 60H 60 routinely feasible. In the latter molecule, it is found that on average only ≈8% of the primitives survive the thresholding algorithm capable of reproducing the exact properties within 10 −6 au.