Human Eye Vision Research Articles

Image Analysis in Histopathology and Cytopathology: From Early Days to Current Perspectives.

Both pathology and cytopathology still rely on recognizing microscopical morphologic features, and image analysis plays a crucial role, enabling the identification, categorization, and characterization of different tissue types, cell populations, and disease states within microscopic images. Historically, manual methods have been the primary approach, relying on expert knowledge and experience of pathologists to interpret microscopic tissue samples. Early image analysis methods were often constrained by computational power and the complexity of biological samples. The advent of computers and digital imaging technologies challenged the exclusivity of human eye vision and brain computational skills, transforming the diagnostic process in these fields. The increasing digitization of pathological images has led to the application of more objective and efficient computer-aided analysis techniques. Significant advancements were brought about by the integration of digital pathology, machine learning, and advanced imaging technologies. The continuous progress in machine learning and the increasing availability of digital pathology data offer exciting opportunities for the future. Furthermore, artificial intelligence has revolutionized this field, enabling predictive models that assist in diagnostic decision making. The future of pathology and cytopathology is predicted to be marked by advancements in computer-aided image analysis. The future of image analysis is promising, and the increasing availability of digital pathology data will invariably lead to enhanced diagnostic accuracy and improved prognostic predictions that shape personalized treatment strategies, ultimately leading to better patient outcomes.

Predicting Weld Quality in Duplex Stainless Steel Butt Joints During Laser Beam Welding: A Hybrid DNN-HEVA Approach

Duplex stainless steel (DSS) welding is critical for producing structures and components in a variety of industries. Because traditional optimization approaches cannot manage the complexity of welding, additional solutions must be investigated. This study addresses the need for a systematic exploration of the welding parameters affecting the quality and performance of DSS butt joints, specifically employing fiber laser welding. This study focuses on butt joints in UNS S32304 and 304L using a fiber laser. Welding process parameters were systematically varied, including laser power, scanning speed, beam diameter, and focal position. To efficiently examine the parameters in the design space, the response surface methodology (RSM) with Box–Behnken design (BBD) was used. The combination of the specific parameter values used in the 7th run (Laser Power: 1600 W, Scanning Speed: 2000 mm/min, Beam Diameter: 1.5 [Formula: see text]m, Focal Position: 30 mm) led to better yield point stress (YPS), maximum tensile stress (MTS), break stress (BS) and reduction in area (RA). ANOVA and lack of fit analysis confirmed the significance of the experiment. In particular, the selected welding parameters significantly influenced all responses. A hybrid machine learning method of deep neural network (DNN) and human eye vision algorithm (HEVA) was used for predicting weld quality during laser beam welding (LBW). The hybrid DNN-HEVA consistently outperformed other optimization methods (RSM-BBD, FNN, CNN, and RNN) across key welding quality parameters. High [Formula: see text]2 values (0.9922, 0.9962, 0.9983, and 0.9907) indicated a strong correlation between predicted and actual values for all calculated responses. Lower RMSE, MSE, and MAE values were also highlighted in the precision of predicted values to the experimental data.

Underwater image classification based on image enhancement and information quality evaluation

Underwater target imaging is widely used in oceans, rivers and lakes detection fields, but due to the existence of water on light absorption scattering attenuation effect, the diffraction limit of imaging system, aberration distortion and underwater turbulence, underwater images has serious degradation, mainly manifested in noise, fuzzy and low resolution, etc. In recent years, some scholars have started from the image enhancement and restoration to improve the image degradation and improve the image clarity, but the effect still needs to be improved, and the resolution can not be improved, and some algorithms will even reduce the resolution.Resolution is an important parameter for the image evaluation, improving the image quality in the underwater imaging, especially in the human eye vision, which is largely determined by the improved resolution. Therefore, this paper starts from each aspects of image processing, studies, proposes and experiments a large number of image recovery algorithms. This paper analyzes various factors introducing noise in underwater imaging process, proposes block mixed filter image denoising method based on noise statistical characteristics, analyzes the necessity of evaluating image quality by using objective indicators, and gives the corresponding objective evaluation parameters according to the characteristics of the image recovery algorithm. According to the noise preprocessing method and the image quality evaluation method, the underwater image synthesis dataset is screened to improve the performance of the underwater object recognition model.

Multiform Art Design Strategy of VR Technology Based on Visual Design Perspective

Abstract This study uses an end-to-end stereo parallax estimation algorithm using deep learning to construct a mechanism to simulate human eye vision in a virtual reality (VR) environment. By applying the hierarchical detail processing (LOD) algorithm related to human vision, the reconstruction of the virtual reality scene is realized to make it closer to the actual observation effect of the human eye. This technology is widely used in various artistic creations, providing the audience an immersive experience. In practical application, the audience experience of the VR opera “The Drunken Princess” received high ratings of more than 4 points in all dimensions. Among them, the audience’s recognition rating for the production was the highest, reaching 4.438 points. On the dimension of narrative experience, the average rating of VR opera was 4.393, compared to 4.1445 for traditional opera on the same dimension. This result highlights the potential of VR technology in enhancing the narrative experience. In addition, a survey on the awareness of VR painting in different industries found that 54% and 43% of practitioners in the art and design industries were aware of VR painting. In contrast, among non-art professions, the level of awareness was only 22.1% in the education industry and 36.2% in other sectors. This indicates that VR painting is more prevalent in the art and design. Participating in VR painting exhibitions and enjoyment by scanning QR codes was also widely accepted by the public, with a satisfaction score of 47.9167. The study found that providing VR art experiences through easy access can effectively attract and fulfill the needs of a wider audience.

Study on InSAR image fusion for improved visualization of active landslides in alpine valley areas: A case in the Batang Region, China

InSAR observation with a wide range and high sensitivity is one of the main techniques for active landslide identification, but due to the influence of the SAR satellite side-view imaging method and observation angle, single-track images in alpine valley areas facing geometric distortion, such as shadowing, layover, and foreshortening, which leads to ineffective observation in some areas. Combining the ascending and descending observation results is expected to compensate for this deficiency to a large extent. This work constructs a pixel-level image fusion method to achieve the fusion of InSAR ascending and descending orbit deformation results, consisting of three algorithms: the DMPI (decision matrix-guided pixel-level InSAR image fusion algorithm), the DMFS (deformable median filter based on decision feedback), and the QSDS (superpixel-based dual-space InSAR image fusion quality evaluation algorithm). To verify the effect, the Batang section of the Jinsha River with high mountain canyon terrain and frequent active landslides is selected. The results show that using the DMPI fused InSAR ascending and descending orbit images can improve spatial perception by enhancing the texture gradient value of remote sensing images by a maximum of two orders of magnitude, compared with the single-track InSAR observation images. Meanwhile, the number of landslides identified increased by 31.5%, and the total area increased by 50.9% on average, improving the accuracy of target detection and identification. In noise reduction, DMFS improves fusion image readability and feature detail by removing SPN (salt and pepper noise) while preserving target edge detail. Furthermore, the QSDS which can evaluate the quality of InSAR fusion images from the perspective of human eye vision, provides an adequate basis for determining the interpretability of InSAR images. This fusion method can partially improve the question of incomplete ground observation due to radar line of sight occlusion in the high mountain canyon area, thus better presenting the InSAR observation results and helping to comprehensively and conveniently interpret the InSAR deformers.

Data Security Using Color Image Based on Beaufort Cipher, Column Transposition and Least Significant Bit (LSB)

One of cryptography algorithm which used is beaufort cipher. Beaufort cipher has simple encryption procedure, but this algorithm has good enough endurance to attack. Unauthorized people cannot break up decrypt without know matrix key used. This algorithm used to encrypt data in the form of text called plaintext. The result of this algorithm is string called ciphertext which difficult to understood that can causing suspicious by other people. Beaufort cipher encryption tested with avalanche effect algorithm with modified one, two, three and all key matrix which resulting maximum 31.25% with all key modification so another algorithm is needed to get more secure. Least Significant Bit (LSB) used to insert ciphertext created to form of image. LSB chosen because easy to use and simple, just alter one of last bit image with bit from message. LSB tested with RGB, CMYK, CMY and YUV color modes inserted 6142 characters resulting highest PSNR value 51.2546 on YUV color mode. Applying steganography technique has much advantage in imperceptibility, for example the image product very similar with original cover image so the difference can not differentiate image with human eye vision. Image that tested as much ten images, that consist of five 512 x 512 and five 16 x 16 image. While string message that used is 240, 480 and 960 character to test 512 x 512 image and 24, 48 and 88 character to test 16 x 16 image. The result of experiment measured with Mean Square Error (MSE) and Peak Signal Ratio (PSNR) which has minimum PSNR 51.2907 dB it means stego image that produced hood enough. Computation time calculation using tic toc in matlab resulting fastest value 0.041636 to encrypt 2000 character and the longest time is 4.10699 second to encrypt 6000 character and inserting to image. Amount of character and amount of multi algorithm can affecting computation time calculation.

Títul Mobile visual media design based on digital media technology and augmented reality

Abstract The reliance on shape-based parameters for traditional 3D multimedia visual behavior can significantly reduce the stability of image simulation. In this paper, the video feature enhancement method of wavelet and human eye vision is used to set the initialization parameters of the ant colony method calculation and calculate the video pixel to different food source distances as a way to obtain the amount of information of each path. The interface pixel affiliation is calculated to make a judgment on whether the amount of information is greater than the initial threshold. The contrast between the detail components of the interface at different scales is enhanced using the wavelet multistage method, and the video visual feedback enhancement is achieved by extracting the interface edge regions in each scale through the local shareholding method. Then the multimedia video representation of human behavior as silhouette sequence, extract the human behavior motion trajectory as large-scale multimedia visual behavior features, and extract the edge features of multimedia vision, and express the results as visual detail features in multimedia video. Finally, a multimedia visual human behavior state model is formed, and the patio-temporal sequence of the model is estimated by fusing it with particle filtering approximation inference to complete the behavioral simulation analysis of multimedia vision. The experimental results show that the average recognition rate of the method in this paper is as high as 98%, the accuracy of behavioral feature extraction is as high as 96%, and the error rate of modeling is 0.02%.

The relationship between spatial color mixing with color and radiation similarity in digital camouflage study

With the development of optical detection technology, the camouflage design in the visible light band has been unable to meet the requirements of the visible light/infrared dual-band digital camouflage detection. The digital camouflage in the human eye vision system involves factors such as the color, shape and texture of the target and background, of which color dominates. And because spatial color mixing is one of the main features of digital camouflage, it is also a key method to improve the camouflage effect. In this paper, a quantitative spatial color mixing coefficient (SCMC) method is proposed to characterize the degree of color mixing of spatial colors. The relationship between spatial color mixing coefficient and color similarity in the visible light range and the relationship between spatial color mixing coefficient and radiation similarity in the infrared range are analyzed. The relationship provides theoretical support for the design and deployment of military equipment on the battlefield. The results show that in the visible light band, the spatial color mixing coefficient can better represent the spatial color mixing degree of digital camouflage, and has a specific relationship with color similarity. In the infrared band, the spatial color mixing coefficient cannot well represent the spatial color mixing degree of digital camouflage, but it can predict its relationship with radiation similarity.

SCDNet: Self-Calibrating Depth Network with Soft-Edge Reconstruction for Low-Light Image Enhancement

Captured low-light images typically suffer from low brightness, low contrast, and blurred details due to the scattering and absorption of light and limited lighting. To deal with these issues, we propose a self-calibrating depth network with soft-edge reconstruction for low-light image enhancement. Concretely, we first employ the soft edge reconstruction module to reconstruct the soft edge of the input image and extract the texture and detail information of the image. Afterward, we explore the convergence properties of each input via the self-calibration module to significantly improve the computational effectiveness of the method and gradually correct the inputs at each subsequent level. Finally, the low-light image is iteratively enhanced by an iterative light enhancement curve to obtain a high-quality image. Extensive experiments demonstrate that our SCDNet visually enhances the brightness and contrast, restores the actual color, and makes the image more in line with the characteristics of the human eye vision system. Meanwhile, our SCDNet outperforms the compared methods in some qualitative and quantitative metrics.

Diagnosing Chronic Glaucoma Using Watershed and Convolutional Neural Network

Abstract: Glaucoma is a disease that relates to the vision of human eye,Glaucoma is a disease that affects the human eye's vision. This sickness is regarded as an irreversible condition that causes eyesight degeneration. One of the most common causes of lifelong blindness is glaucoma in persons over the age of 40. Because of its trade-off between portability, size, and cost, fundus imaging is the most often utilised screening tool for glaucoma detection. Fundus imaging is a two-dimensional (2D) depiction of the three-dimensional (3D), semitransparent retinal tissues projected on to the imaging plane using reflected light. The idea plane that depicts the physical display screen through which a user perceives a virtual 3D scene is referred to as the "image plane”. The bulk of current algorithms for autonomous glaucoma assessment using fundus images rely on handcrafted segmentation-based features, which are influenced by the segmentation method used and the retrieved features. Convolutional neural networks (CNNs) are known for, among other things, their ability to learn highly discriminative features from raw pixel intensities. This work describes a computational technique for detecting glaucoma automatically. The major goal is to use a "image processing technique" to diagnose glaucoma using a fundus image as input. It trains datasets using a convolutional neural network (CNN). The Watershed algorithm is used for segmentation and is the most widely used technique in image processing. The following image processing processes are performed: region of interest, morphological procedures, and segmentation. This technique can be used to determine whether or not a person has Glaucoma. Keywords: Recommender system, item-based collaborative filtering, Natural Language Processing, Deep learning.

Adjustment of Lighting Parameters from Photopic to Mesopic Values in Outdoor Lighting Installations Strategy and Associated Evaluation of Variation in Energy Needs

The sensitivity of the human eye varies with the different lighting conditions to which it is exposed. The cone photoreceptors perceive the color and work for illuminance conditions greater than 3.00 cd/m² (photopic vision). Below 0.01 cd/m², the rods are the cells that assume this function (scotopic vision). Both types of photoreceptors work coordinately in the interval between these values (mesopic vision). Each mechanism generates a different spectral sensibility. In this work, the emission spectra of common sources in present public lighting installations are analyzed and their normative photopic values translated to the corresponding mesopic condition, which more faithfully represents the vision mechanism of our eyes in these conditions. Based on a common street urban configuration (ME6), we generated a large set of simulations to determine the ideal light point setup configuration (luminance and light point height vs. poles distance ratio) for each case of spectrum source. Finally, we analyze the derived energy variation from each design possibility. The results obtained may contribute to improving the criterion of light source selection and adapting the required regulatory values to the human eye vision process under normalized artificial street lighting condition, reaching an average energy saving of 15% and a reduction of 8% in terms of points of light required. They also offer a statistical range of energy requirements for lighting installation that can be used to generate accurate electrical designs or estimations without the necessity of defining the exact lighting configuration, which is 77.5% lower than conventional design criteria.

Influence of Human Visual Perception and Eye Tracking Motion on the Quality of Moving Image in LCD

There is a very important index in the influence of human visual perception, that is, the degree of the motion blur about the moving image on display device. In this paper, a new kind of improved method is proposed to calculate the response time of liquid crystal under the new backlight driving and modulation, which is more accurate than the traditional moving window integration method. This paper also discusses the eye tracking movement of the human visual system, including studying the influence of image content, size, motion speed and motion direction, based on the human vision property study and the analyzes of the simulation model of image motion artifacts perceived by human eyes. Experiments are performed, using the human eye vision perception measurement system. The experiment data shows that the edge blur time can be reduced to 10.5 ms, compared with the 16.5 ms in traditional drive, reduced by 36.4%, and the human perception of motion blur can be markedly reduced. Also, the results show that the simulation results are in good agreement with the actual measurement data by modifying the proportion coefficient of the eye tracking object model to 0.9. At the same time, through the improved human eye tracking model of smooth moving objects, the actual motion blur phenomenon perceived by the human eye can be calculated more accurately, and the results can be used in image processing algorithms to improve the quality of the moving image on the display.

The Role of Hyperspectral Imaging: A Literature Review

Optical analysis techniques are used recently to detect and identify the objects from a large scale of images. Hyperspectral imaging technique is also one of them. Vision of human eye is based on three basic color (red, green and blue) bands, but spectral imaging divides the vision into many more bands. Hyperspectral remote sensors achieve imagery data in the form of hundreds of adjoining spectral bands. In this paper, our purpose is to illustrate the fundamental concept, hyperspectral remote sensing, remotely sensed information, methods for hyperspectral imaging and applications based on hyperspectral imaging. Moreover, in the forensic context, the novel methods involving deep neural networks are elaborated in this paper. The proposed idea can be useful for further research in the field of hyperspectral imaging using deep learning.

Recovery of a spectrum based on a compressive-sensing algorithm with weighted principal component analysis

The purpose of this study is to improve the reconstruction precision and better copy the color of spectral image surfaces. A new spectral reflectance reconstruction algorithm based on an iterative threshold combined with weighted principal component space is presented in this paper, and the principal component with weighted visual features is the sparse basis. Different numbers of color cards are selected as the training samples, a multispectral image is the testing sample, and the color differences in the reconstructions are compared. The channel response value is obtained by a Mega Vision high-accuracy, multi-channel imaging system. The results show that spectral reconstruction based on weighted principal component space is superior in performance to that based on traditional principal component space. Therefore, the color difference obtained using the compressive-sensing algorithm with weighted principal component analysis is less than that obtained using the algorithm with traditional principal component analysis, and better reconstructed color consistency with human eye vision is achieved.

The Impact on Human Eye Vision of Different Paper Reflective Brightness under Different Lamps

Test reflective brightness, on the market, infant and children’s books, primary and secondary school textbooks, reference books and reading materials, under the 5 watt yellow bold table lamp respectively with the grating and without the granting, and the ordinary 20 watt yellow bulb table lamp. Proposed to improve the manufacturing process of recycled printing paper in China, do not add fluorescent powder, infant and children’s books had better not use halftone paper, and two-colored printing had better not use celadon two-colored printing.

White light generation via up-conversion and blue tone in Er3+/Tm3+/Yb3+-doped zinc-tellurite glasses

Yb3+, Er3+ and Tm3+ triply doped zinc-tellurite glass have been prepared containing up to 3.23 wt% of rare-earth ion oxides, were characterized by absorption spectroscopy, excitation, emission and up-conversion spectra. Transparent and homogeneous glasses have been produced, managing the red, green and blue emission bands, in order to generate white light considering the human eye perception. The energy transfer (resonant or non-resonant) between those rare-earth ions provides a color balancing mechanism that maintains the operating point in the white region, generating warm white light, cool white light and artificial daylight through the increase of the 976/980 nm diode laser excitation power from 4 to 470 mW. A light source at 4000 K is obtained under the excitation at 980 nm with 15 mW, providing a white light environment that is comfortable to the human eye vision. The spectroscopic study presented in this work describes the white light generation by the triply-doped zinc-tellurite glass, ranging from blue, green and red, by controlling the laser excitation power and wavelength at 976/980 nm. Such white tuning provokes healthy effects on human health throughout the day, especially the circadian system.

The role of (ACES) color space in controlling the color quality of digital cinema image.

Over the last decade of the technological evolution appeared a number of Digital Color Spaces which are used to express color values for digital cinematic image, These digital color spaces are used in digital cinematography stage, they are also used in digital cinema projection stage. At the end of 2013, has been innovating the (ACES) digital color space, which enjoy advantages in its colorimetric values approached the color vision of the human eye vision, this made (ACES) able to work in parallel with the stages of digital photography and digital cinema projection. This requires the study of (ACES) digital color system and comparing it with the digital color systems previously used before the advent of (ACES) to determine the importance of the (AECS) digital color space in controlling the quality of the digital cinematic image. Objectives: The research aims to study the advantages and the color borders of (ACES) digital color space, and compare it with the color borders of the digital color spaces previously used before (ACES) appearance to determine the extent of its importance in controlling the quality of the digital cinematic image, both in digital cinematography stage or in digital cinema projection stage. Methodology: The researchers followed the descriptive method to describe the features and capabilities and color border of ACES digital color space and its uses at the stages of digital photography and digital projection in order to control the final image quality of digital cinema image before it is being presented and projected. Results: • ACES digital color space is the perfect color system optimized to handle film's technology production in parallel at the stages of digital photography and digital projection. • By studying the color boundaries of ACES digital color system, which strongly approaches the limits of the color vision of the human eye we can substitute (ACES) with the digital color spaces (Rec.709), (Rec.2020) which are used in digital cinematography stage, also we can substitute (ACES) with the digital color spaces (YCbCr), (DCI-P3) which are used in digital cinema projection stage.

Directional view method for a time-sequential autostereoscopic display with full resolution.

A time-sequential autostereoscopic three-dimensional (3D) display using a set of cylindrical optical elements (COEs) as the backlight steering is proposed. The operation principle of the system and its detailed design are described. In our system, the COEs control the direction of the backlight for the proposed system of the user's right and left views. Additionally, the displayed images can be observed under ambient lighting by implementing the high density light-emitting diode (LED) arrays. Compared to the first-generation array display, the image resolution is greatly improved by the addition of the time multiplexing technique. A prototype system using a set of COEs, LED arrays, two linear Fresnel lenses, and an elliptical diffuser is constructed. Here, the directional backlight beams are synchronized with the right and left images alternately displayed on the liquid crystal display (LCD) screen, and two convergent viewing zones are formed alternately in front of the user's eyes; then 3D images are perceived because of persistence of the vision of human eye. The experimental results show that the proposed method is a potential technology for 3D applications such as 3D television.

Automatic Face Recognition System using Pattern Recognition Techniques: A Survey

Automatic Face Recognition system is widely applied in new technologies. This system works beyond the ability of human vision. The limited vision of human eye in identifying vast number of human faces is overcome by the automatic face recognition with many more advantages. The basic purpose of face recognition system is to compare the image video which is stored in a database with the image video in real time variation. Many techniques have been used in face recognition system. This paper present a survey of several techniques used in face recognition system, an approach to the detection and identification of human face. Keywordsrecognition, face detection, face extraction.

Effect of heat-treatment on the structural and optical properties of Cu2S thin films deposited by CBD method

Semiconducting Cu2S thin films were successfully deposited on glass substrate under three different conditions such as as-deposited, post heat-treated and pre heated precursor solution by chemical bath deposition technique. Structural and optical properties of the films were characterized by X-ray diffraction (XRD), scanning electron microscope, energy dispersive X-ray (EDX) analysis and UV–Visible spectrophotometer. The XRD spectra showed the amorphous nature of thin films with hexagonal structure. The d value and micro strain increased and the average crystallite size decreased from 1.9 to 1.4 and 1.3 nm respectively when the as-deposited film was subjected to post heat-treatment and the precursor solution temperature was elevated. The presence of more nucleation centers and fast reaction rate decreased the average crystallite size in films grown with pre heated precursor solution. The noticed blue shift in energy gap and the shift of XRD peak position towards the lower 2θ side by heat-treatment could be considered as a sign of the quantum confined effect due to the formation of the nano-sized Cu2S crystals on the surface. The transmittance of heat-treated Cu2S films in the visible region matched the phototropic vision of human eye (~600 nm) which makes them suitable for solar control coatings on architectural windows and automobiles in the regions with warm climates. Low transmittance behaviour of pre heated Cu2S films could be used for anti dazzling coatings for car windscreens and driving mirrors to reduce the dazzling effects of light at night. EDX spectra showed the chemical purity of the films. The observed broad absorption and blue shift in band gap of the heat-treated films were due to quantum confinement effect. Fourier transform infrared studies were also carried out and the results are presented.