Three-dimensional Color Images Research Articles

Using a Chaotic Digital System to Generate Random Numbers for Secure Communication on 5G Networks

There are several encryption system applications in 5G networks where rapid response is needed, particularly in the military, health sector, traffic, and vehicular movement. This article presents a proposed data security system for 5G networks that fortifies the security of the network through the use of synchronized chaotic systems to produce pseudo-random numbers. The technique by which random numbers are generated during the encryption procedures is closely associated with 5G network security. Many synchronized chaotic systems are used to produce chaotic random models which are used as encryption bases for a wide variety of data. In this study, the encryption was carried out using a variety of data, including two and three-dimensional color images and audio signals of varying lengths, in addition to the use of Fast Fourier Transform (FFT) for encryption of the ingredient energy wave. The results revealed that the algorithm deployed in the process of encryption performed well. Simulations were performed in MATLAB.

Computer-generated holography with ordinary display.

We propose a method of computer-generated holography (CGH) using incoherent light emitted from a mobile phone screen. In this method, we suppose a cascade of holograms in which the first hologram is a color image displayed on the mobile phone screen. The hologram cascade is synthesized by solving an inverse problem with respect to the propagation of incoherent light. We demonstrate a three-dimensional color image reproduction using a two-layered hologram cascade composed of an iPhone and a spatial light modulator.

An Improved Encoder-Decoder CNN with Region-Based Filtering for Vibrant Colorization

Colorization is the practice of adding appropriate chromatic values to monochrome photographs or videos. A real-valued luminance image can be mapped to a three-dimensional color image. However, it is a severely ill-defined problem and not has a single solution. In this paper, an encoder-decoder Convolutional Neural Network (CNN) model is used for colorizing gray images where the encoder is a Densely Connected Convolutional Network (DenseNet) and the decoder is a conventional CNN. The DenseNet extracts image features from gray images and the conventional CNN outputs a * b * color channels. Due to a large number of desaturated color components compared to saturated color components in the training images, the saturated color components have a strong tendency towards desaturated color components in the predicted a * b * channel. To solve the problems, we rebalance the predicted a * b * color channel by smoothing every subregion individually using the average filter. 2 stage k-means clustering technique is applied to divide the subregions. Then we apply Gamma transformation in the entire a * b * channel to saturate the image. We compare our proposed method with several existing methods. From the experimental results, we see that our proposed method has made some notable improvements over the existing methods and color representation of gray-scale images by our proposed method is more plausible to visualize. Additionally, our suggested approach beats other approaches in terms of Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM) and Histogram.

A Dynamic Detection Method for Phenotyping Pods in a Soybean Population Based on an Improved YOLO-v5 Network

Pod phenotypic traits are closely related to grain yield and quality. Pod phenotype detection in soybean populations in natural environments is important to soybean breeding, cultivation, and field management. For an accurate pod phenotype description, a dynamic detection method is proposed based on an improved YOLO-v5 network. First, two varieties were taken as research objects. A self-developed field soybean three-dimensional color image acquisition vehicle was used to obtain RGB and depth images of soybean pods in the field. Second, the red–green–blue (RGB) and depth images were registered using an edge feature point alignment metric to accurately distinguish complex environmental backgrounds and establish a red–green–blue-depth (RGB-D) dataset for model training. Third, an improved feature pyramid network and path aggregation network (FPN+PAN) structure and a channel attention atrous spatial pyramid pooling (CA-ASPP) module were introduced to improve the dim and small pod target detection. Finally, a soybean pod quantity compensation model was established by analyzing the influence of the number of individual plants in the soybean population on the detection precision to statistically correct the predicted pod quantity. In the experimental phase, we analyzed the impact of different datasets on the model and the performance of different models on the same dataset under the same test conditions. The test results showed that compared with network models trained on the RGB dataset, the recall and precision of models trained on the RGB-D dataset increased by approximately 32% and 25%, respectively. Compared with YOLO-v5s, the precision of the improved YOLO-v5 increased by approximately 6%, reaching 88.14% precision for pod quantity detection with 200 plants in the soybean population. After model compensation, the mean relative errors between the predicted and actual pod quantities were 2% to 3% for the two soybean varieties. Thus, the proposed method can provide rapid and massive detection for pod phenotyping in soybean populations and a theoretical basis and technical knowledge for soybean breeding, scientific cultivation, and field management.

Incoherent computer-generated holography.

We present a method for computer-generated holography (CGH) using spatially and temporally incoherent light. The proposed method synthesizes a hologram cascade by solving an inverse problem for the propagation of incoherent light. The spatial incoherence removes speckle noise in CGH, and the temporal incoherence simplifies the optical setup, including the light source. We demonstrate two- and three-dimensional color image reproductions by a two-layer grayscale hologram cascade with a chip-on-board white light-emitting diode.

Fault Line Selection of Distribution Network Based on Modified CEEMDAN and GoogLeNet Neural Network

Aiming at the difficulty of single-phase grounding fault line selection in a small current grounding system, a distribution network fault line selection method based on modified CEEMDAN and convolutional neural network is proposed. Firstly, the random forest and multiscale permutation entropy are used to modify the Complete Ensemble Empirical Mode Decomposition Adaptive Noise algorithm (CEEMDAN), and the zero-sequence current of each line is decomposed into a series of intrinsic mode functions through the modified CEEMDAN (MCEEMDAN) algorithm. Secondly, the intrinsic mode function is transformed into the image formation by using the signal-image conversion method, and the generated image is upgraded to a three-dimensional color image by combining pseudo-color coding technology. Finally, the color images converted from the signals of each line are fused as the input of the GoogLeNet network, and the fault line selection of the distribution network is realized in the form of probability output by the Softmax function. The experimental results show that the proposed method has not only strong feature extraction ability and high recognition accuracy but also has good anti-noise and robustness.

Facial Tightening Effects, Following Focused and Radial Acoustic Wave Therapy Assessment, Using a Three‐Dimensional Digital Imaging

Background and ObjectivesAcoustic wave therapy is a novel facial tightening technique that involves nonthermal penetration of the skin and subcutaneous tissue, affecting cells and their metabolism, and resulting in an increased release of unwanted fat and activation of blood and lymphatic flow in tissues. The objective of this study was to investigate the effectiveness of acoustic wave therapy.Study Design/Materials and MethodsA total of 333 patients underwent multiple facial tightening treatment sessions using focused and radial acoustic waves. Each patient received 2,000–3,000 pulses of focused acoustic waves at a power of 0.45–0.88 mJ/mm2 with a pulse frequency of 3–5 Hz and 4,000 pulses of radial acoustic waves at 4‐bar power at a frequency of 21 Hz. These sessions were performed more than three times, and treatments were repeated at 1‐month intervals. Digital photographs superimposed three‐dimensional volumetric assessments, and three‐dimensional skin surface displacement calculations using vectors were used to evaluate the results 12 months after the last treatment. Patients also evaluated the results using a 5‐point Likert scale.ResultsImprovements in skin texture, clarity, and laxity were observed in digital photographs. Superimposed three‐dimensional color images showed marked volumetric reduction and/or formative modification for even contour toward the lower mid‐face. Most vectors showed three‐dimensional skin surface displacement at the lateral sides of the temples, cheeks, and chin, in an upward direction. These results were obtained and sustained for up to 12 months without edematous reactions. Almost all patients reported improvement, with 79% reporting “good” or “excellent” improvement. Complications were minor and transitory. Persistent side effects were not observed.ConclusionAcoustic wave therapy could be used as a standard facial tightening treatment, with skin rejuvenation effects shown on digital photographs and three‐dimensional quantification assessments. This noninvasive acoustic wave approach was found to be a safe, long‐lasting, and effective method for facial tightening. Lasers Surg. Med. 00:00–00, 2020. © 2020 Wiley Periodicals LLC

Facial Tightening Following a Single Acoustic Wave Treatment Using Focused and Radial Acoustic Waves

Background: Acoustic wave has been used for many medical purposes, and although it is widely applied in cosmetic procedures, it has not been conducted for facial rejuvenation and tightening. Acoustic wave has been proven to penetrate deeper than subcutaneous tissue, independent of skin color, and to be beneficial for skin tightening and body contouring. Objective: To evaluate the effectiveness of a single acoustic wave treatment session using unique focused and radial acoustic waves for facial tightening. Participants: Sixty Asian patients were treated between the years 2016 and 2018. The single acoustic wave treatment session consists of focused long planar acoustic pulses thought to have an effect on cells and their metabolism resulting in an increased release of fat, and radial short acoustic pulses thought to have an effect on tissues activating blood and lymphatic flow. Patients did not undergo any form of medical aesthetic treatment during the study. Measurements: Digital photographs and three-dimensional imaging were used to evaluate the results. Results: Objective assessments with digital photographs and superimposed three-dimensional color images showed preferable facial tightening effects and marked volumetric reduction on the lower one-third of the face. These results were obtained without the edematous reactions observed in laser and radiofrequency therapies, and were sustained up to 12 months. All of the patients reported satisfaction with the results and convenience of the procedure. Complications were minor and transitory, consisting of a slight tingly sensation to the teeth during the treatment, and mild erythema resolving within 5 hours. Side effects were not observed. Conclusions: The advantages of the single acoustic wave treatment are the high potency of facial tightening effects, reduction of discomfort and side effects. Taken together, these characteristics facilitate the ability to give repeated treatments and provide an alternative or adjunct treatment for patients with improved results.

Full-color large-scaled computer-generated holograms using RGB color filters.

A technique using RGB color filters is proposed for creating high-quality full-color computer-generated holograms (CGHs). The fringe of these CGHs is composed of more than a billion pixels. The CGHs reconstruct full-parallax three-dimensional color images with a deep sensation of depth caused by natural motion parallax. The simulation technique as well as the principle and challenges of high-quality full-color reconstruction are presented to address the design of filter properties suitable for large-scaled CGHs. Optical reconstructions of actual fabricated full-color CGHs are demonstrated in order to verify the proposed techniques.

The robust reconstruction of disparity maps using multilevel processing of color image stereopairs

A novel approach, which makes it possible to realize the reconstruction of disparity maps for subsequent visualization of three-dimensional color images in real time, is proposed and substantiated.

Multidimensional color image storage, retrieval, and compression based on quantum amplitudes and phases

In this study, we propose a new representation method for multidimensional color images, called an n-qubit normal arbitrary superposition state (NASS), where n qubits represent the colors and coordinates of 2n pixels (e.g., a three-dimensional color image of 1024×1024×1024 using only 30 qubits). Based on NASS, we present an (n+1)-qubit normal arbitrary superposition state with relative phases (NASSRP) and an (n+2)-qubit normal arbitrary superposition state with three components (NASSTC) for lossless and lossy quantum compression, respectively. We also design three general quantum circuits to generate NASS, NASSRP, and NASSTC states, where we retrieve an image from a quantum system using different projection measurement operators. Finally, we define the quantum compression ratio and analyze lossless and lossy quantum compression algorithms of multidimensional quantum images. For the first time, we implemented the compression of multidimensional color images on a quantum computer. Thus, we address the theoretical and practical aspects of image processing on a quantum computer.

Multi-dimensional color image storage and retrieval for a normal arbitrary quantum superposition state

Multi-dimensional color image processing has two difficulties: One is that a large number of bits are needed to store multi-dimensional color images, such as, a three-dimensional color image of $$1024 \times 1024 \times 1024$$1024?1024?1024 needs $$1024 \times 1024 \times 1024 \times 24$$1024?1024?1024?24?bits. The other one is that the efficiency or accuracy of image segmentation is not high enough for some images to be used in content-based image search. In order to solve the above problems, this paper proposes a new representation for multi-dimensional color image, called a $$(n\,+\,1)$$(n+1)-qubit normal arbitrary quantum superposition state (NAQSS), where $$n$$n qubits represent colors and coordinates of $${2^n}$$2n pixels (e.g., represent a three-dimensional color image of $$1024 \times 1024 \times 1024$$1024?1024?1024 only using 30?qubits), and the remaining 1?qubit represents an image segmentation information to improve the accuracy of image segmentation. And then we design a general quantum circuit to create the NAQSS state in order to store a multi-dimensional color image in a quantum system and propose a quantum circuit simplification algorithm to reduce the number of the quantum gates of the general quantum circuit. Finally, different strategies to retrieve a whole image or the target sub-image of an image from a quantum system are studied, including Monte Carlo sampling and improved Grover's algorithm which can search out a coordinate of a target sub-image only running in $$O(\sqrt{N/r} )$$O(N/r) where $$N$$N and $$r$$r are the numbers of pixels of an image and a target sub-image, respectively.

Color 3D Image Encryption Technique by Combined Use of Computational Integral Imaging Joint Image Scrambling Technique

In this paper, we propose a novel three-dimensional (3D) color image encryption scheme based on computational integral imaging (CII) and Arnold transform technique. An elemental image array (EIA) is firstly captured by recording the light rays emanating from 3D image through a lenslet array. Then, the captured color EIA is decomposed into three independent channels: red, green and blue, and each channel is encrypted by Arnold transform. In the reconstruction process, the pseudo-inverse filter is used to improve quality of the reconstructed 3D color image in CII system. Numerical simulations have been done to prove the validity and the security of the proposed 3D color image encryption method.

Key Technologies Research on Color Contour Map of 3D Injection Molding Simulation Results

According to the color contour map of the 3D injection molding simulation results, the commonly used color contour map drawing algorithm was researched, and a three-dimensional color image rendering algorithm which based on the "physical field values and color range mapping" was given too. And the key technologies of the algorithm which was used to draw 3D color contour map were introduced in detail. In the end, an example was given.

User interface for a three-dimensional colour ultrasound imaging system

A three-dimensional ultrasound imaging system color user interface (104) generates a volumetrically-rendered ultrasound image (76). The ultrasound image (76) is manipulable using three-dimensional image compositing functions. The interface (104) presents to the user three-dimensional image controls for controlling the ultrasound image. The three-dimensional image controls (104) have an operational similarity to two-dimensional image controls for controlling a two-dimensional ultrasound image. The interface (104) further relates the three-dimensional ultrasound image controls to the plurality of three-dimensional image compositing functions for manipulating the ultrasound images. Additionally, the interface presents to the user a three-dimensional color image control for controllably manipulating the ultrasound image using three-dimensional image using compositing functions such as (1) a color flow mapping function (76, FIGURE 11), (2) a color flow overlay function for mapping fluid flow direction (76, FIGUREs 12 and 13), (3) a depth-based velocity visualization color mapping function (76, FIGURE 14A); and (4) an absolute velocity representation function for mapping absolute fluid flow velocity relating to said ultrasound object (76, FIGURE 15).

A Three-dimensional Color Image Display by Laser Breakdown Plasma in Liquid

A Three-dimensional Color Image Display by Laser Breakdown Plasma in Liquid

Tomografia computadorizada da coluna lombar após artrodese com emprego de material metálico: avaliação da qualidade da imagem para diferentes algoritmos matemáticos

OBJETIVO: Selecionar os melhores algoritmos para o exame de coluna lombar na avaliação de artrodese com material metálico. MATERIAIS E MÉTODOS: Utilizou-se um equipamento de tomografia computadorizada de 16 fileiras de detectores. Imagens de dez pacientes foram reconstruídas com filtros 20, 40, 60 e 80 e realizadas reformatações em três dimensões e multiplanares com espessuras de 2 mm e 4 mm. Um total de 320 imagens foi avaliado por três experientes radiologistas, que deram notas de 1 a 5 (1 = não-aceitável; 2 = abaixo dos padrões; 3 = aceitável; 4 = acima da média; 5 = excelente). Além disso, foram realizadas medidas de ruído para correlação com o tipo de filtro utilizado. RESULTADOS: As médias do valor de ruído para reconstrução com 2 mm e filtros 20, 40, 60 e 80 foram de 24,7 ± 4,3; 35,5 ± 4,2; 106,0 ± 18,5 e 145,9 ± 26,9, respectivamente, e para 4 mm foram de 18,1 ± 2,4; 25,1 ± 4,6; 76,7 ± 17,2 e 106,6 ± 23,4. CONCLUSÃO: As imagens coloridas em três dimensões são mais bem visualizadas com filtro 20, entretanto, nas imagens em tons de cinza um filtro intermediário de 40 ou 60 pode ser útil para demonstrar os parafusos com maior detalhe. Para reconstruções multiplanares com espessura de 2 mm o filtro 40 é mais bem aceito, e para uma espessura de 4 mm um filtro 60 apresentou melhor qualidade.

An Adaptive Two-Stage Edge Detection Scheme for Digital Color Images

An adaptive two-stage edge detection scheme for digital color images is proposed in this paper. In the first stage of this scheme, each three-dimensional color image is reduced to a one-dimensional gray-level image using the moment-preserving thresholding technique. Then, a new edge detection technique based on the block truncation coding scheme is introduced to detect the edge boundary in the second stage. The edge detection process makes use of the bit plane information of each BTC-encoded block to detect the edge boundary. The experimental results show that the performance of the detected edge image of the proposed scheme is as good as in Yang's scheme and in the Sobel operator. However, the computational cost consumed by the proposed scheme is less than that of Yang's scheme. In addition, the proposed scheme provides an adaptive edge quality decision mechanism. This mechanism can provide different edge images to meet various applications and the subjective evaluation. Moreover, this scheme locates the edge boundaries to the sub-pixel accuracy, which is an advantage to applications such as data hiding and image watermarking.

220 カラー画像処理を用いた気泡流3次元計測システムの開発

This paper presents a measuring system for bubbly flow by a three-dimensional color image processing. The system is based on an usual particle tracking velocimetry (PTV). Fluorescent micro-capsules are used as the particles to track the motions of liquid. The micro-capsules shine with yellow green by an ultra-violet illumination. Incandescent lights with red-colored cellophane sheets are used as back lighting. Using the above mentioned illumination, the bubbles are colored by black, the micro-capsules by yellow green, and the background by red. A high-speed color video camera with four mirrors is used to obtain two images taken from two different directions that are diagonal from each other. The obtained images are transformed temporary to Windows-BMP files. The BMP files are divided into three different text data that represent the color values of red, green and blue, respectively. The bubbles and micro-capsules are extracted separately by using these three different data. Although the bubbles and particles are extracted precisely, the motions of them are not calculated well because diagonal two images are not sufficient for the 3-D tracking.

格子傾斜モアレトポグラフィによる水位分布の計測と画像表示

Topographic measurement of water surface is essential to study wave motion. In order to measure simultaniously the whole area of wave surface, the inclined grid method of moire topography discriminating between rise and fall of water surface with high sensitivity is the most suitable technique.As the results of experiments, the inclined grid method proved adequately fit for practical use with accuracy better than ±1%.The digital image processing techniques of the moiré fringes data was developed to determine the quantities of the ups and downs of water surface, then the three-dimensional color image of the contour variation was obtained by using computer graphic techniques.The topographic measurement and visualization system was applied to the wave motion in a wave generation device utilizing a resonant duct and the three-dimensional color images of its contour variation were obtained.