Sight Research Articles

Adaptive histogram equalization with visual perception consistency

Histogram equalization (HE) is a well-established method for image contrast enhancement due to its simplicity and effectiveness. However, it suffers from three main shortcomings, i.e., over-enhancement, under-enhancement and mean shift. To address these issues, this paper proposes a systematic scheme, that is, adaptive histogram equalization with visual perception consistency (AHEVPC). Firstly, a novel histogram correction model is designed to get the optimal controlling parameters, which specifically address the aforementioned issues of HE. Besides, considering the subjective perception of the initial output of the model, two strategies are proposed to make the enhanced image more natural and comfortable. Finally, histogram equalization is applied to the modified histogram. Extensive experimental results demonstrate that the proposed scheme is reasonable and effective, and outperforms several state-of-the-art methods in terms of subjective and objective metrics.

Figure-ground segmentation based on motion in the archerfish.

Figure-ground segmentation is a fundamental process in visual perception that involves separating visual stimuli into distinct meaningful objects and their surrounding context, thus allowing the brain to interpret and understand complex visual scenes. Mammals exhibit varying figure-ground segmentation capabilities, ranging from primates that can perform well on figure-ground segmentation tasks to rodents that perform poorly. To explore figure-ground segmentation capabilities in teleost fish, we studied how the archerfish, an expert visual hunter, performs figure-ground segmentation. We trained archerfish to discriminate foreground objects from the background, where the figures were defined by motion as well as by discontinuities in intensity and texture. Specifically, the figures were defined by grating, naturalistic texture, and random noise moving in counterphase with the background. The archerfish performed the task well and could distinguish between all three types of figures and grounds. Their performance was comparable to that of primates and outperformed rodents. These findings suggest the existence of a complex visual process in the archerfish visual system that enables the delineation of figures as distinct from backgrounds, and provide insights into object recognition in this animal.

Silvia De Marchi (1929) on numerical estimation: A translation and commentary.

Vittorio Benussi (1878-1927) is known for numerous studies on optical illusions, visual and haptic perception, spatial and time perception. In Padova, he had a brilliant student who carefully worked on the topic of how people estimate numerosity, Silvia De Marchi (1897-1936). Her writings have never been translated into English before. Here we comment on her work and life, characterized also by the challenges faced by women in academia. The studies on perception of numerosity from her thesis were published as an article in 1929. We provide a translation from Italian, a redrawing of its 23 illustrations and of the graphs. It shows an original experimental approach and an anticipation of what later became known as magnitude estimation.

Presynaptic Proteins and Their Roles in Visual Processing by the Retina.

The sense of vision begins in the retina, where light is detected and processed through a complex series of synaptic connections into meaningful information relayed to the brain via retinal ganglion cells. Light responses begin as tonic and graded signals in photoreceptors, later emerging from the retina as a series of spikes from ganglion cells. Processing by the retina extracts critical features of the visual world, including spatial frequency, temporal frequency, motion direction, color, contrast, and luminance. To achieve this, the retina has evolved specialized and unique synapse types. These include the ribbon synapses of photoreceptors and bipolar cells, the dendritic synapses of amacrine and horizontal cells, and unconventional synaptic feedback from horizontal cells to photoreceptors. We review these unique synapses in the retina with a focus on the presynaptic molecules and physiological properties that shape their capabilities.

Pose Estimation-Based Visual Perception System for Analyzing Fish Swimming

Pose Estimation-Based Visual Perception System for Analyzing Fish Swimming

Temporal sensitivity for achromatic and chromatic flicker across the visual cortex.

The retinal ganglion cells (RGCs) receive different combinations of L, M, and S cone inputs and give rise to one achromatic and two chromatic post-receptoral channels. Beyond the retina, RGC outputs are subject to filtering and normalization along the geniculo-striate pathway, ultimately producing the properties of human vision. The goal of the current study was to determine temporal sensitivity across the three post-receptoral channels in subcortical and cortical regions involved in vision. We measured functional magnetic resonance imaging (MRI) responses at 7 Tesla from three participants (two males, one female) viewing a high-contrast, flickering, spatially-uniform wide field (∼140°). Stimulus flicker frequency varied logarithmically between 2 and 64 Hz and targeted the L+M+S, L-M, and S-[L+M] cone combinations. These measurements were used to create temporal sensitivity functions of primary visual cortex (V1) across eccentricity, and spatially averaged responses from lateral geniculate nucleus (LGN), V2/V3, hV4, and V3A/B. Functional MRI responses reflected known properties of the visual system, including higher peak temporal sensitivity to achromatic vs. chromatic stimuli, and low-pass filtering between the LGN and V1. Peak temporal sensitivity increased across levels of the cortical visual hierarchy. Unexpectedly, peak temporal sensitivity varied little across eccentricity within area V1. Measures of adaptation and distributed pattern activity revealed a subtle influence of 64 Hz achromatic flicker in area V1, despite this stimulus evoking only a minimal overall response. Comparison of measured cortical responses to a model of integrated retinal output to our stimuli demonstrates that extensive filtering and amplification is applied to post-retinal signals.Significance Statement We report the temporal sensitivity of human visual cortex across the three canonical post-receptoral channels from central vision to the far periphery. Functional MRI measurements of responses from the LGN, V1, and higher visual cortical areas demonstrate modification of temporal sensitivity across the visual hierarchy. This includes amplification of chromatic signals between the LGN and V1, and an increase in peak temporal sensitivity in visual areas beyond V1. Within V1, we find a surprising stability of peak temporal sensitivity in the periphery for all three post-receptoral directions. Comparison of our results to a model of retinal output demonstrates the presence of substantial post-retinal filtering, yielding greater uniformity of responses across area V1 than would be predicted from unmodified retinal signals.

A Phosphenotron Device for Sensoric Spatial Resolution of Phosphenes within the Visual Field Using Non-Invasive Transcranial Alternating Current Stimulation

This study presents phosphenotron, a device for enhancing the sensory spatial resolution of phosphenes in the visual field (VF). The phosphenotron employs a non-invasive transcranial alternating current stimulation (NITACS) to modulate brain activity by applying weak electrical currents to the scalp or face. NITACS’s unique application induces phosphenes, a phenomenon where light is perceived without external stimuli. Unlike previous invasive methods, NITACS offers a non-invasive approach to create these effects. The study focused on assessing the spatial resolution of NITACS-induced phosphenes, crucial for advancements in visual aid technology and neuroscience. Eight participants were subjected to NITACS using a novel electrode arrangement around the eye orbits. Results showed that NITACS could generate spatially defined phosphene patterns in the VF, varying among individuals but consistently appearing within their VF and remaining stable through multiple stimulations. The study established optimal parameters for vibrant phosphene induction without discomfort and identified electrode positions that altered phosphene locations within different VF regions. Receiver Operating characteristics analysis indicated a specificity of 70.7%, sensitivity of 73.9%, and a control trial accuracy of 98.4%. These findings suggest that NITACS is a promising, reliable method for non-invasive visual perception modulation through phosphene generation.

Assessing Trial-by-Trial Electrophysiological and Behavioral Markers of Attentional Control and Sensory Precision in Psychotic and Mood Disorders.

The current study investigated the extent to which changes in attentional control contribute to performance on a visual perceptual discrimination task, on a trial-by-trial basis in a transdiagnostic clinical sample. Participants with schizophrenia (SZ; N = 58), bipolar disorder (N = 42), major depression disorder (N = 51), and psychiatrically healthy controls (N = 92) completed a visual perception task in which stimuli appeared briefly. The design allowed us to estimate the lapse rate and the precision of perceptual representations of the stimuli. Electroencephalograms (EEG) were recorded to examine pre-stimulus activity in the alpha band (8-13 Hz), overall and in relation to behavior performance on the task. We found that the attention lapse rate was elevated in the SZ group compared with all other groups. We also observed group differences in pre-stimulus alpha activity, with control participants showing the highest levels of pre-stimulus alpha when averaging across trials. However, trial-by-trial analyses showed within-participant fluctuations in pre-stimulus alpha activity significantly predicted the likelihood of making an error, in all groups. Interestingly, our analysis demonstrated that aperiodic contributions to the EEG signal (which affect power estimates across frequency bands) serve as a significant predictor of behavior as well. These results confirm the elevated attention lapse rate that has been observed in SZ, validate pre-stimulus EEG markers of attentional control and their use as a predictor of behavior on a trial-by-trial basis, and suggest that aperiodic contributions to the EEG signal are an important target for further research in this area, in addition to alpha-band activity.

Positive Effect of Super-Resolved Structural Magnetic Resonance Imaging for Mild Cognitive Impairment Detection

This paper presents a novel approach to improving the detection of mild cognitive impairment (MCI) through the use of super-resolved structural magnetic resonance imaging (MRI) and optimized deep learning models. The study introduces enhancements to the perceptual quality of super-resolved 2D structural MRI images using advanced loss functions, modifications to the upscaler part of the generator, and experiments with various discriminators within a generative adversarial training setting. It empirically demonstrates the effectiveness of super-resolution in the MCI detection task, showcasing performance improvements across different state-of-the-art classification models. The paper also addresses the challenge of accurately capturing perceptual image quality, particularly when images contain checkerboard artifacts, and proposes a methodology that incorporates hyperparameter optimization through a Pareto optimal Markov blanket (POMB). This approach systematically explores the hyperparameter space, focusing on reducing overfitting and enhancing model generalizability. The research findings contribute to the field by demonstrating that super-resolution can significantly improve the quality of MRI images for MCI detection, highlighting the importance of choosing an adequate discriminator and the potential of super-resolution as a preprocessing step to boost classification model performance.

Integrating Image Perception and Time‐to‐First‐Spike Coding in MoS2 Phototransistors for Spiking Neural Network

AbstractHuman vision system remains alert for dangers and adopts high‐speed and low‐power coding methods to convert the image information to spike signals. To meet the demand for danger alert in machine vision, it is important to design intelligent sensors to integrate the functions of image perception and high‐efficiency coding for high‐priority analysis. Inspired by the human visual system, a MoS2 phototransistor is introduced on SiNx substrate enabling simultaneous image perception and time‐to‐first‐spike (TTFS) coding. The device demonstrates exceptional performance in encoding 3‐bit grayscale images, achieving a low mean squared error of 0.008 and a high structural similarity index of 0.9784. Spiking neural networks (SNN) with TTFS coding achieve high recognition accuracy (98.86%) while reducing spike count by 75%. The device array also perceives motion direction and object states by converting data temporally. This work establishes a hardware foundation to promote the performance of SNNs in efficiently identifying crucial information.

The Semantic Structure of the Image of “Vision” in the Russian Linguistic Worldview

This article examines the structure of the image of “vision” in the Russian linguistic worldview. The structural reconstruction was performed through the study of the key meanings of “vision” in the Russian language. The proposition, a logical outline of the components involved in visual perception, was selected as a way by which the knowledge about “vision” is gathered. The following components were found to be a regular source of figurative meanings: the subject of visual perception, the process of visual perception, the subject’s features indicating the quality of visual perception, and the means of visual perception. The dominant meanings of different propositional elements constituting the structural core of the image of “vision” were revealed: “the ability to see,” “the quality of vision,” “light,” “mediation,” and “accommodation.” The main denotative spheres covered by the knowledge about “vision” were distinguished: the human sphere, as well as the spheres of artifacts (technical means of image capture, artificial light sources) and nature (primarily natural light sources). It was shown that the metaphors referring to the human sphere are based on the idea of a close connection between visual perception and mental activity. The anthropomorphic metaphors arising from the artifacts used to produce images are created following the same logical pattern. The metaphorical understanding of light sources, both artificial and natural, is determined by the association between “vision” and light in the minds of native Russian speakers. 

Flexible retinomorphic vision sensors with scotopic and photopic adaptation for a fully flexible neuromorphic machine vision system

AbstractBioinspired neuromorphic machine vision system (NMVS) that integrates retinomorphic sensing and neuromorphic computing into one monolithic system is regarded as the most promising architecture for visual perception. However, the large intensity range of natural lights and complex illumination conditions in actual scenarios always require the NMVS to dynamically adjust its sensitivity according to the environmental conditions, just like the visual adaptation function of the human retina. Although some opto‐sensors with scotopic or photopic adaption have been developed, NMVSs, especially fully flexible NMVSs, with both scotopic and photopic adaptation functions are rarely reported. Here we propose an ion‐modulation strategy to dynamically adjust the photosensitivity and time‐varying activation/inhibition characteristics depending on the illumination conditions, and develop a flexible ion‐modulated phototransistor array based on MoS2/graphdiyne heterostructure, which can execute both retinomorphic sensing and neuromorphic computing. By controlling the intercalated Li+ ions in graphdiyne, both scotopic and photopic adaptation functions are demonstrated successfully. A fully flexible NMVS consisting of front‐end retinomorphic vision sensors and a back‐end convolutional neural network is constructed based on the as‐fabricated 28 × 28 device array, demonstrating quite high recognition accuracies for both dim and bright images and robust flexibility. This effort for fully flexible and monolithic NMVS paves the way for its applications in wearable scenarios.

Reflections of well-being: navigating body image, chronic energy deficiency, and nutritional intake among urban and rural adolescents

BackgroundAdolescent growth and development is a period of very specific nutritional problems. As a result of poor growth and development, 36.3% of adolescents in Indonesia are at risk of developing CED. The purpose of this study was to determine the description of body image, the incidence of Chronic Energy Deficiency (CED), and nutritional intake in adolescents in urban and rural areas.MethodsThis study used a descriptive quantitative design with a cross-sectional study conducted in Bandung and Sumedang on 387 adolescents aged 13–15 years. The instruments used in this study were body image questionnaire Figure Rating Scale (FRS) method, 2 × 24-h food recall, and anthropometry for Measuring mid upper arm circumference (MUAC).ResultsResults of this study showed that more than half of adolescents in urban (54.0%) and rural areas (61.7%) were at risk of CED, had negative body image perceptions in urban (69.1%) and rural areas (62.3%), and underconsumption of macronutrients in both urban and rural adolescents.ConclusionMost adolescents in urban and rural areas still consume less energy, carbohydrates, and protein. Perceived body image and nutrient intake contribute to the incidence of CED in adolescents.

Objects as human bodies: cross-linguistic colexifications between words for body parts and objects

Abstract Many languages have words that denote a human body part and an object, for example, hand, which refers to a part of a person and a watch. As of yet, there is no systematic study on the distribution of these shared names, i.e., colexifications, between two concrete semantic domains in a variety of languages. Here, I present a study that investigates colexifications between body and object concepts, i.e., body-object colexifications. By using a newly established workflow, colexifications are automatically extracted based on a seed list containing 134 body concepts and 650 object concepts. The analysis focuses on the frequency, distribution, cognitive relations, and coincidental cases of 78 body-object colexifications occurring across 396 language varieties. The results show that some body-object colexifications are widespread, but most occur in a small number of language varieties. By creating a network structure to examine individual relations and additionally comparing ratings of visual and haptic perception across concepts, the study indicates that the similarity of visual perception plays a central role in the emergence of body-object colexifications. The findings provide a first general overview of the phenomenon and offer ample opportunities for future research.

The Influence of Service Quality, Customer Relationship Management (CRM), and Image on Patient Satisfaction and Service Marketing Performance at A Type B Private Hospital in Makassar

Purpose: The overarching purpose of this research encompasses a multifaceted examination aimed at understanding various factors influencing patient satisfaction and service marketing performance in private hospitals in Makassar. Specifically, the objectives are to explore the impact of service quality, customer relationship management (CRM), and image on patient satisfaction, as well as to analyze their influence on service marketing performance.
  
 Methods: Primary data for this study were collected through a survey conducted among 160 inpatients across four Type B private hospitals in Makassar. The survey was administered between April and June 2022. Data analysis was conducted using Structural Equation Modeling (SEM), a statistical technique utilized to examine complex relationships among variables.
  
 Results and Discussion: The findings of the research revealed several significant insights: (1) Service quality, CRM, and image each had a direct impact on patient satisfaction at private hospitals in Makassar. (2) Furthermore, patient satisfaction was found to significantly influence service marketing performance. (3) Additionally, the study identified indirect effects, such as the influence of service quality, CRM, and image on service marketing performance mediated through patient satisfaction.
  
 Implications of the Research: These findings hold important implications for private hospitals in Makassar. Understanding and enhancing service quality, CRM practices, and image perception can directly contribute to improving patient satisfaction, which in turn positively impacts service marketing performance. By recognizing and addressing these factors, hospitals can better align their strategies to meet patient needs and enhance overall performance.
  
 Originality/Value: This research contributes to the existing literature by providing comprehensive insights into the dynamics between service quality, CRM, image, patient satisfaction, and service marketing performance in the context of private hospitals in Makassar. The study's findings offer valuable guidance for hospital management in devising effective strategies to optimize patient satisfaction and enhance service marketing outcomes, ultimately improving overall organizational performance.

Halo effect measurement for mini‐light‐emitting diode backlight liquid crystal displays

AbstractWe develop a measurement and evaluation system to quantify the halo effect of mini‐light‐emitting diode (LED) backlight liquid crystal displays (mLCDs). The validity and reliability of our halo measurement system was investigated through a human visual perception experiment. The results indicate that our halo measurement system can effectively distinguish the halo differences among different displays, with matching rate of 93.3% between our measurement and the human visual system.

Obstacle Detection Technology for Autonomous Driving Based on Deep Learning

With the rapid growth of artificial intelligence (AI) technology, traditional obstacle detection equipment faces multiple challenges such as high cost, low real-time performance, non normalization, dependence on manual operation, and time-consuming and labor-intensive. To address these shortcomings, this article proposes a deep learning (DL) based obstacle detection technology for autonomous driving on the road surface. As a complex system that integrates multiple key components such as environmental perception, positioning and navigation, path planning, and motion control, one of the core technologies of autonomous vehicles is accurate perception of the surrounding environment. In practical applications, autonomous vehicles often face complex and variable road environments, which may lead to a decrease in the quality of images captured by cameras, resulting in blurry and unclear phenomena. The DL method, especially the object detection algorithm, has shown unique advantages in visual perception and recognition in autonomous driving scenes. This paper deeply studies the obstacle detection technology of automatic driving road based on DL, aiming to achieve efficient and accurate obstacle recognition, improve the safety and reliability of auto drive system, and promote the further growth of automatic driving technology.

PBDB-T/Pentacene-Based Organic Optoelectronic Synaptic Transistor with Adjustable Critical Flicker Fusion Frequency for Dynamic Vision.

In the era of the Internet of Things and the rapid progress of artificial intelligence, there is a growing demand for advanced dynamic vision systems. Vision systems are no longer confined to static object detection and recognition, as the detection and recognition of moving objects are becoming increasingly important. To meet the requirements for more precise and efficient dynamic vision, the development of adaptive multimodal motion detection devices becomes imperative. Inspired by the varied response rates in biological vision, we introduce the concept of critical flicker fusion frequency (cFFF) and develop an organic optoelectronic synaptic transistor with adjustable cFFF. In situ Kelvin probe force microscopy analysis reveals that light signal recognition in this device originates from charge transfer in the poly[(2,6-(4,8-bis(5-(2-ethylhexyl)thiophen-2-yl)benzo[1,2-b:4,5-b']dithiophene)-co-(1,3-di(5-thiophene-2-yl)-5,7-bis(2-ethylhexyl)-benzo[1,2-c:4,5-c']dithiophene-4,8-dione)] (PBDB-T)/pentacene heterojunction, which can be effectively modulated by gate voltage. Building upon this, we implement different cFFF within a single device to facilitate the detection and recognition of objects moving at different speeds. This approach allows for resource allocation during dynamic detection, resulting in a reduction in power consumption. Our research holds great potential for enhancing the capabilities of dynamic visual systems.

A taxonomic revision of the Palaearctic species of the ant genus Tapinoma Mayr 1861 (Hymenoptera: Formicidae)

A taxonomic revision of the Palaearctic species of the ant genus Tapinoma Emery 1861 is provided. Due to the extreme rarity of discernable characters, the female castes of 64% of the species are not separable by primary visual perception of an expert and are thus truly cryptic. The main working rationale of the revision is Numeric Morphology-Based Alpha-Taxonomy (NUMOBAT) with formation of species hypotheses largely based on exploratory data analyses and checking these hypotheses by discriminant analysis. NUMOBAT data of all considered species comprise 648 worker samples with 2014 individuals and 30,000 primary data. Species are depicted by z-stack imaging in three standard visual positions. Numeric data on 15 phenotypical characters are presented in comparative tables and supplementary verbal descriptions are given. Analysis of nuclear DNA was based on evaluation of 15 microsatellite loci in 274 nest samples. The NUMOBAT-based classification of eight species of the Tapinoma nigerrimum and T. simrothi group which are inseparable by subjective visual inspection was confirmed by nuclear DNA data in 98.3% of 169 samples where both morphological and nuDNA data were available. The three cases of disagreement between NUMOBAT and nuDNA classification were discussed. Excluding Nomina Nuda and unavailable names, the revision recognized 34 available names which divide into 21 valid species, 11 junior synonyms and two names placed under Incertae Sedis. Four species are described as new: Tapinoma hispanicum n. sp., T. insularis n. sp., T. dabashanica n. sp. and T. sichuense n. sp. The following synonymies were stated: T. collina Foerster 1850, T. erraticum platyops Emery 1925 and T. erraticum bononiensis Emery 1925 as synonyms of T. erraticum (Latreille 1798); T. tauridis Emery 1925 and T. breve Emery 1925 as synonyms of T. glabrella (Nylander 1849) that is erected to species level; T. minor Bernard 1945 as synonym of T. simrothi Krausse-Heldrungen 1911; T. simrothi azerbaidzhanica Karavajev 1932 as synonym of Tapinoma karavaievi Emery 1925 that is erected here to species level; T. erraticum ambiguum Emery 1925 as synonym of T. madeirense Forel 1895 and T. emeryanum Kuznetzov-Ugamsky 1927 as synonym of T. sinense Emery 1925. Despite an insufficient separation of the female castes of Tapinoma madeirense and T. subboreale Seifert 2011 by NUMOBAT characters and detection of a hybrid zone in southern France, the heterospecific status of the two taxa was maintained based on sufficient differences in male genitalia and of nuclear DNA over a larger geographic scale. Formica caerulescens Losana 1834 is removed from genus Tapinoma and recognized as member of the subfamily Formicinae.

Appearance comparison on social networking sites and body shame: The role of negative body talk and perceived sociocultural influences on body image.

Social media platforms play a significant role in the lives of young people. While the usage of these platforms has grown, research exploring the challenges of body image remains limited. This study investigated whether initiating negative body talk functioned as an indirect pathway between appearance comparison on social media and body shame and whether perceived sociocultural influences from parents, friends, and media on body image moderated this indirect effect. An online cross-sectional survey of 795 Chinese college students (Mage = 20.17, SD = 1.65; 60% female, 40% male) was conducted. Negative body talk was a partial indirect pathway in the association, and this indirect effect was significant among those experiencing higher sociocultural pressures from all three sources. This study highlights the need for health psychology in understanding and addressing the mental health consequences associated with digital media and sociocultural influences on body image perception.