Digital Image Processing Applications Research Articles

An Efficient VLSI Design of 32X32 bit Multiplier using Wallace Tree Algorithm in Vivado HLS and Xilinx ISE Software using VHDL

Multiplier is the most basic component present in any digital system. These multipliers are mainly used in Digital Signal and Image Processing applications. In applications like image detection latest sophisticated algorithms like CNN are used which contains MAC units in their design. The multiplier used in MAC unit requires huge memory, offers high latency and consumes more power. There are many algorithms such as Combinational, Sequential and Array Multiplication Algorithms which helps in designing Multiplier. The major drawback in all designs is circuit complexity. The problem of latency and power dissipation are also present. Considering all the drawbacks present in those algorithms this paper proposes the usage of Wallace Tree Algorithm which consumes less power and has low latency. Also, there are many ways to add the final stage of partial products generated such as Carry Look Ahead adder, Carry Select Adder etc. This paper uses both Carry Select Adder and Ripple Carry Adder for performing final addition of partial products. All previous partial products are added using Half adders and Full adders. The Multiplier is designed using VHDL in Xilinx ISE and Vivado Platform.

An efficient circuit for error reduction in logarithmic multiplication for filtering applications

SummaryReal‐time digital signal and image processing applications, such as filtering, demand high performance. Often, multiplication is one of the most time‐consuming steps of the filtering operation. Log‐based multipliers have been used for improving multiplication efficiency at the expense of accuracy. The objective of the proposed work is to improve the accuracy of log‐based hardware multipliers by appropriately altering the filter weights and without increasing the required resources.

A New Method for Designing Dense Skeleton Asphalt Mixture Based on Meso Parameter

At present, research on the internal structures of asphalt mixtures has mostly focused on the statistical analysis of their mesostructural components such as aggregates, voids, and asphalt mortars, in addition to the verification of the mechanical behaviour of the mixture through simulations. Furthermore, the capacity of the research has not risen to a level where a design method to guide the design and optimisation of the asphalt mixture gradation has been formulated. After an in-depth analysis of the existing evaluation parameters and standards for the asphalt mixture skeleton, this study proposes a new method for precise designing a dense skeleton asphalt mixture (DSAM) based on meso parameter. The results indicate that the application of digital image processing (DIP) techniques to adjust the gradation increases the average coordination number (n¯c) and reduces the ratio of the quantity of coarse aggregate without contact point to the total quantity of coarse aggregate (C value). This can effectively improve the meso parameters of the mixture so that the quality of the main skeleton is significantly enhanced; the process also has higher precision and demands less test work. VCAmix(IMAGE) ≤ VCADRC and n¯c>1.6 while C < 20% can be used as qualitative and quantitative evaluation criterion for forming better main skeleton structure of coarse aggregate. The new method of designing a DSAM based on meso parameter is intuitive and convenient, which considerably reduces the blindness and tediousness in the design of the asphalt mixture gradation. The engineering example also proves that the asphalt mixture has an excellent pavement performance and verifies the feasibility of the proposed design method.

An Improved Enhancement Algorithm Based on CNN Applicable for Weak Contrast Images

Image enhancement is commonly used in digital image processing applications. Through image enhancement, the features of the target object are enhanced to make it easier to identify. In order to realize image enhancement, a neural network with a trapezoidal convolution kernel is proposed in this paper. First, weak contrast images are generated using the images in SIDD, DND and RENOIR, which are public datasets used for image denoising. On this basis, pixel distribution characteristics of the R, G and B channels of the weak contrast images are analyzed, and the histogram distribution of the images is given, which can be used to determine the size of the network convolution kernels. Then, a multi-layer convolution neural network is constructed, which uses the original image as an input and outputs the noise map. This network includes convolution kernels of different sizes for the three channels of the original images, and the convolution kernel size is determined by calculating the mean square deviation of the pixels of the corresponding channel. The proposed algorithm provides visually pleasing contrast enhancement. In this paper, a public dataset for image enhancement and actual captured images are separately assessed, both the contrast experiment and ablation experiment results show that the algorithm proposed in this paper can achieve a higher Peak Signal to Noise Ratio (PSNR) and a higher Structural Similarity Index (SSIM) than other image enhancement algorithms.

Reconfigurable half-precision floating-point real/complex fused multiply and add unit

Multiplication followed by an addition/subtraction is the common operation in many digital signal and image processing applications. This paper presents a reconfigurable floating-point real/complex fused multiply and add (R/C-FMA) unit using small precision (IEEE-754-2008 16-bit half-precision) format. The developed FMA can be reconfigurable from real to complex based on the control bits. This architecture performs real FMA [(a × b) + c], complex FMA {[(a + ib) × (c + id)] + (e + if)} or mixed real and complex FMA {[(a + ib) × (c + id)] + e}. The field programmable gate array (FPGA) implementation of R/C-FMA design, utilises the modern features of inbuilt DSP blocks for mantissa multiplication and addition/subtraction. The efficient DSP usage for fp16 FMA design shows a 60% reduction in LUT area when compared to conventional fp32 FMA.

Reconfigurable half-precision floating-point real/complex fused multiply and add unit

Multiplication followed by an addition/subtraction is the common operation in many digital signal and image processing applications. This paper presents a reconfigurable floating-point real/complex fused multiply and add (R/C-FMA) unit using small precision (IEEE-754-2008 16-bit half-precision) format. The developed FMA can be reconfigurable from real to complex based on the control bits. This architecture performs real FMA [(a × b) + c], complex FMA {[(a + ib) × (c + id)] + (e + if)} or mixed real and complex FMA {[(a + ib) × (c + id)] + e}. The field programmable gate array (FPGA) implementation of R/C-FMA design, utilises the modern features of inbuilt DSP blocks for mantissa multiplication and addition/subtraction. The efficient DSP usage for fp16 FMA design shows a 60% reduction in LUT area when compared to conventional fp32 FMA.

Effects of Saururus chinensis BAILL Extract in Rats with Experimentally Chronic Constipation: An application of Clinical Pathology and Digital Image Processing

Effects of <i>Saururus chinensis BAILL</i> Extract in Rats with Experimentally Chronic Constipation: An application of Clinical Pathology and Digital Image Processing

Applications (Ideas) in Linear Algebra with Digital Image Processing. Can we Do, Teach, Motivate and Evaluate?

The application of new methodologies in higher education brings with it questions such as: “Can we do it?”, “Can we teach?”, “Can we motivate students?”, “Can we evaluate?”. During the last 8 years, in the Linear Algebra course of the Mechanical and Electromechanical Engineering of the Polytechnic of Coimbra-Institute of Engineering, it has been trying to answer these questions. The teaching methodology presented consists in the approach of Linear Algebra contents, using digital Image Processing applications. This new environment is intended to encourage students to learn the concepts and their manipulation in a productive and dynamic way. From the analysis of the studies and the student’s opinions (students’ adherence and motivation, questionnaires), it has been found that the use of this new teaching methodology helps the ‘learning to learn’ as long as it is well defined, with clear objectives for those who implements (teacher) and who interacts (students) with it.

Klasifikasi Kematangan Stroberi Berbasis Segmentasi Warna dengan Metode HSV

Classification of Strawberry Maturity Based on Color Segmentation using HSV Method. Manual fruit maturity classification has many limitations because it is influenced by human subjectivity. Hence, the application of digital image processing and artificial intelligence becomes more effective and efficient. This study aims to create a classification system that automatically divides strawberry maturity into three categories, namely not ripe, half-ripe, and ripe. The process of identifying the level of fruit maturity is based on the color characteristics Red, Green, Blue (RGB) value of the image. The method used for color segmentation is Hue, Saturation, Value (HSV) and for the classification of strawberry maturity using the Multi-Class Support Vector Machine (SVM) algorithm with a Radial Basic Function (RBF) kernel. Strawberry image data was retrieved using the Logitech C920 camera. The dataset consisted of 158 images of strawberries. The results showed that the classification of strawberry maturity using the multi-class SVM algorithm with kernel parameters RBF cost (C) = 10 and gamma (γ) = 10-3 produced the highest accuracy of 97%.

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Field Programmable Gate Array Applications—A Scientometric Review

Field Programmable Gate Array (FPGA) is a general purpose programmable logic device that can be configured by a customer after manufacturing to perform from a simple logic gate operations to complex systems on chip or even artificial intelligence systems. Scientific publications related to FPGA started in 1992 and, up to now, we found more than 70,000 documents in the two leading scientific databases (Scopus and Clarivative Web of Science). These publications show the vast range of applications based on FPGAs, from the new mechanism that enables the magnetic suspension system for the kilogram redefinition, to the Mars rovers’ navigation systems. This paper reviews the top FPGAs’ applications by a scientometric analysis in ScientoPy, covering publications related to FPGAs from 1992 to 2018. Here we found the top 150 applications that we divided into the following categories: digital control, communication interfaces, networking, computer security, cryptography techniques, machine learning, digital signal processing, image and video processing, big data, computer algorithms and other applications. Also, we present an evolution and trend analysis of the related applications.

Technology supporting health services for rural areas based on image processing

Limited health facilities, both medical equipment and health workers in developing countries and other rural areas in the world, bring significant problems for public health services. In order to make a correct diagnosis, it is necessary to support accurate data from health equipment that should be available at the health care centre. On the other hand, the development of technology, especially in the field of digital image processing is quite rapid. This paper discusses the application of digital image processing in solving problems concerning the limitations of health care facilities. In this paper, we will discuss the application of digital image processing in cataract screening, image quality improvement of ultrasonography, identification of leukocyte cells, and identification of ventricular areas and the hippocampus of magnetic resonance imaging images. The results show that the implementation of digital image processing techniques can help overcome some of the problems that arise due to the limitations of these health facilities.

Segmentasi Citra Medis untuk Deteksi Objek FAM pada Payudara Menggunakan Metode Sobel

Fibroa Adenoma Mammae (FAM) or called a benign tumor is the most common tumor found in the breast, often this disease is considered as breast cancer by some laymen, but this disease is different from cancer because Fibroadenoma (FAM) can grow in all parts of the breast, In identifying FAM, doctors or radiologists usually have to analyze carefully the images of Magnetic Resonance stored in the format of Digital Imaging Communication In Medicine (DICOM). This process is certainly quite time consuming. Thus the author feels the need to create a digital image processing application to help doctors or radiologists identify FAM in the breast by utilizing the segmentation process in medical images of USG results using the Sobel method. This method performs the original image segmentation process by detecting the edges of the image then the segmentation results are converted into binary images so the system can determine the FAM area. Medical image segmentation using the Sobel method is good for determining the edges of FAM objects because the edges can be clearly seen but for some image images with less resolution as previously tested, edge detection will be difficult to determine the edges of smooth objects and only form lines rough edges.

An Efficient Design of DCT Approximation Based on Quantum Dot Cellular Automata (QCA) Technology

Optimization for power is one of the most important design objectives in modern digital image processing applications. The DCT is considered to be one of the most essential techniques in image and video compression systems, and consequently a number of extensive works had been carried out by researchers on the power optimization. On the other hand, quantum-dot cellular automata (QCA) can present a novel opportunity for the design of highly parallel architectures and algorithms for improving the performance of image and video processing systems. Furthermore, it has considerable advantages in comparison with CMOS technology, such as extremely low power dissipation, high operating frequency, and a small size. Therefore, in this study, the authors propose a multiplier-less DCT architecture in QCA technology. The proposed design provides high circuit performance, very low power consumption, and very low dimension outperform to the existing conventional structures. The QCADesigner tool has been utilized for QCA circuit design and functional verification of all designs in this work. QCAPro, a very widespread power estimator tool, is applied to estimate the power dissipation of the proposed circuit. The suggested design has 53% improvement in terms of power over the conventional solution. The outcome of this work can clearly open up a new window of opportunity for low power image processing systems.

Digital Image Processing Application on Shallots Quality Determination

Shallot is a horticultural vegetable commodity that has high economic value. North Sulawesi is one of the central production of shallots which has several onion varieties developed and marketed. Technology that can help determine the quality of shallots is needed to simplify the marketing process. This study aims to simulate a system for determining the quality of shallots based on their color and size. The shallot bulb image of several different varieties is input for this system to be able to provide good and bad shallot marks.

On the design and implementation of a dual fisheye camera-based surveillance vision system

Image processing and computer vision have been a focus of researchers for decades in various application domains. This research is continuously rising with the rise of Artificial Intelligence in the fourth industrial revolution. One of the important digital image processing applications is to produce panorama images. The wide range of view a panorama image provides can be used in a variety range of applications which may include surveillance applications and remote robot operations. A panorama image is a combination of several individual natural looking images into a composite one to provide a wide field of view that may reach 360 degrees horizontally without any distortion. Wide-angle lenses provide a wide field of view, but using them alone does not necessarily make a panorama image. In this work the design and implementation of a wide-angle stereo vision system that suites many real-time applications is proposed. The system makes use of two wide-angle fisheye cameras where each camera covers around 170 degrees field of view. The horizontal angle between the cameras is 140 degrees. The cameras acquire the instantaneous overlapping images continuously and transmits them to a base station via a communication link. The base station calibrates, corrects, correlates and stitches the non-overlapping corrected images to a composite one. The resultant final image covers 310 degrees field of view. The system is of low computational complexity compared with previously implemented systems. It is tested on a laptop and on a standalone embedded computing device. The processing speed for the panorama image stitching including the correction of the fisheye barrel distortion on the laptop computer and the embedded computer is 11 fps, and 6 fps, respectively.

Direct growth of ZnTe on Si(100) and Si(111) substrate by molecular beam epitaxy

ZnTe was directly grown on Si(100) and Si(111) substrate respectively using elemental sources by molecular beam epitaxy. It was found that ZnTe can be grown on both Si(111) and Si(100) substrates in alignment with the orientation of (111). A microscopic growth interface model of diamond crystal structure was proposed to explain this phenomenon. This is a supplement to the existing theory of predicting possible crystalline orientation alignment relationship based on lattice mismatch value in the heteroepitaxial growth on (100) surfaces of zinc blende structure. High resolution transmission electron microscopy (HRTEM) was used to investigate the ZnTe(111)/Si(100) and ZnTe(111)/Si(100) interface. Application of digital image processing involving a filtered inverse fast Fourier transformation revealed an array of misfit dislocations at the ZnTe/Si(111) interface.

Kernel Hilbert space template-matching techniques for simultaneous determination of neutron source location and identity with a volumetrically-sensitive moderating-type neutron spectrometer

Hand-held instrumentation that can provide real-time information regarding the location and identity (i.e., type/radioisotope and local surrounding/shielding) of neutron radiation sources, via free neutron measurements alone, are of interest to non-proliferation, water/oil-exploration and related neutron scattering applications. In a previous report, template-matching techniques in two- and three-spatial dimensions were introduced as methods for simultaneously determining the horizontal-planar location and the identity of neutron radiation sources with a new class of volumetrically-sensitive moderating-type neutron spectrometer . Although these methods were shown to be quite promising for this new class of instrumentation, there are three significant factors that negatively affect their performance in practice: (1) there are a large number of templates of interest for most practical applications; (2) many of these templates are very similar (i.e., highly correlated or strongly degenerate); and, (3) the measurement data is superposed with environmental neutron scattering effects. In this work, kernel Hilbert space transformations, that have been proposed to solve analogous problems in digital image processing applications, are employed to overcome the aforementioned difficulties encountered when analyzing spectroscopic neutron radiation measurements via template-matching techniques, and a novel kernel Hilbert space template-matching algorithm is introduced. Four variants of this improved technique are tested and compared via MCNP6 simulation for efficacy of localization and identification of neutron radiation sources with this new class of neutron spectrometer.

Teledetección aplicada al mapeo geomorfológico de los volcanes de la cuenca alta del río Chaschuil, provincia de Catamarca, Argentina

Contexto: La cuenca alta del río Chaschuil se encuentra en las provincias geomorfológicas de codillera Frontal y sistema de Famatina, se extiende desde el límite superior de la cuenca, a los 26° 45' 6,35" de latitud S y 68° 2'22 15" de longitud O, hasta el volcán Aguas Calientes, a los 27° 13' 25,81" de latitud S y 68° 19'5 48" de longitud O. La zona se inserta en el Cinturón de Fuego del Pacífico, que se caracteriza por concentrar algunas zonas de subducción más importantes del mundo, donde se genera una intensa actividad sísmica y volcánica.&#x0D; Método: A través de operaciones estadísticas y numéricas aplicadas sobre los datos de las matrices que componen una imagen satelital, se generó la cartografía geomorfológica volcánica. Para dicho análisis, se utilizó el software libre SoPI 3.0, en el que se procesaron las imágenes satelitales Landsat 7 y 8, de los años 2002 y 2015. La cartografía fue elaborada en el software libre QGIS 3.2.2, con el apoyo del software libre Google Earth Pro.&#x0D; Resultados: Los mejores resultados del procesamiento digital se dieron en las bandas de rango visible y mediante distintas combinaciones de bandas en RGB. Se describen 13 aparatos volcánicos principales, altamente erosionados, con lavas pahoehoe asociadas; y erupciones secundarias, con lavas rugosas tipo aa sobrepuestas a las lavas más fluidas.&#x0D; Conclusiones: La aplicación del procesamiento digital de imágenes satelitales es una herramienta óptima para el estudio de estructuras volcánicas, que permite su delimitación y clasificación.

Change in the physical­mechanical and decorative properties of labradorite under thermal exposure

We have experimentally investigated samples from the four fields of coarse-grained labradorite, which is extracted in Ukraine. The samples of labradorite were tested at high temperatures of 200, 300, 400, 500, 600, 700, 800, 900 °С. Red spots at the surface of samples is the result of oxidation of the metal Fe 2+ : at different fields of labradorite they cover a different area of the sample's surface of natural stone: it ranges from 39 to 60 %. An analysis of the polished labradorite surface after heating revealed that red inclusions are evenly distributed over the surface of labradorite samples. Oxidation of minerals, which is visually observed on all the samples of labradorite, starts at a temperature of 300 °С. One of the features in the research described in this paper is the application of digital image processing in order to quantitatively assess the Fe oxidation area (red spots) at the polished surface of labradorite samples. To a temperature of 500‒600 °С, there is a gradual increase in the oxidized area of the samples' surface. At temperatures above 700 °С, there is a sharp increase in the oxidized area at the samples' surface. In general, the oxidized spots of metals cover between 40 to 60 % of the surface of labradorite samples. When heated, the labradorite samples become 50 % brighter than the original value for indicator L in the color system Lab. A decrease in the velocity of ultrasonic wave propagation in labradorite samples occurs evenly, without surges. The reason for a decrease in the ultrasonic wave velocity is the formation of defects and cracks in labradorite samples due to an uneven thermal expansion of minerals. At a temperature of 700 °С ° or higher, there is a decrease in the velocity of ultrasound wave propagation in the samples of natural stone. At heating, there is a decrease in the indicators for gloss in all labradorite samples. In general, when labradorite was heated up to 900 °С, the samples from the Ocheretyansky deposit lost 11.21 % of their gloss, from the Neviryvsky deposit ‒ 4.03 %, from the Osnikivske deposit ‒ 33.57 %, from the Katerinovsky deposit ‒ 15.3 %.