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Even though both farm and wild raw honeys are better than processed honey in terms of nutritional value and quality, wild honey is more expensive than farm honey due to its scarcity, nutrition, and quality. However, there is a challenge for consumer to differentiate both farm and wild raw honey due to the complexity of raw honey. Although near infrared (NIR) spectroscopy is promising to assist consumers to differentiate types of honeys, the financial barrier to have a NIR spectroscopy is needed to be addressed. Thus, this research aims to evaluate the performance of a low cost NIR light acquisition alternative in classifying stingless bee honeys using artificial neural network (ANN). First, 164 honey samples of two different types of raw honeys were prepared. Next, NIR light LEDs of five different wavelengths i.e. 850, 860, 870, 890, and 950 nm with light sensors were used to acquire the transmitted NIR absorbance from raw honey sample. ANN with different number of hidden neurons were used to analyze the data, and six datasets were used to investigate the best distance between NIR light source and light sensors. Results indicate that the acquired NIR light coupled with ANN by using eight hidden neurons and an average distance of 40 mm from light source to light sensor were able to produce the best result with the best true positive (TP) correct classification percentage accuracy and cross entropy (CE) value of 96.0% and 1.14, respectively.

Nowadays, there are about 100 million diabetes patients and increasing in every day. One of the procedures to diagnose this disease is to measure the blood glucose level. The technology of blood glucose measurement that normally use is invasive to the patient by punctured the fingertip and collect the drop of blood to test. Thus, diabetes patients have a pain in several times a day and in one test. They must buy the strip test and needle. So, the little cost in one day will become the huge cost in one year. And that is the reason to develop a non-invasive way to monitor the blood glucose level that has lower cost and risk of infection for them. This paper presents a new noninvasive blood glucose measuring method by near infrared light 940nm wavelength as emitter transmitting though finger for receiving PPG signals to determine glucose level of blood. Using 12 samples for regression fit curve finds relation between maximum value and minimum value of PPG signals and blood glucose level (mg/dl). Results give accuracy 95.13% which is in high range for accuracy. In this device also can connect wi-fi to store data.

This paper introduces a novel measurement method at the inner pH in the deep area of the tissue-like structure. The proposed method uses fluorescence microsensors using near-infrared light, which represents high tissue transmittance, and reference sensors for compensating the absorption of excitation and emission light to the tissue-like structure. In this paper, fluorescence pH microsensors are fabricated and evaluated the pH sensitivity. Finally, measurement of environmental pH using reference sensors, and detection of fluorescence microsensor at 1.5 mm deep in tissue-like structure are successfully demonstrated.

Absorption of Near Infrared Light (NIR) is stronger when the breech is in the systolic period. In this way, the system can get cyclic finger signals from the tip of the finger, signals that can reflect the absorption of infrared light through the skin, muscle, bone and venous blood, or the absorption of infrared light through arterial blood.

In most of the iris identification systems, the complete image constraints are understood. These Constrain include near-infrared (NIR) illumination to release the iris texture and close distance from the capturing device. In recent advances to different illumination technologies introduced in images captured in the environment. This environment includes a visible wavelength (VW) light source at-a-distance over the close distance from the capturing device. For accurate Iris identification at-a-distance, eye images require improvement of effective strategies. By using implementation of iris-identification-at-a-distance (IAAD) systems. For feature extraction technique for NIR and VW images were taken under uncontrolled environment. For the identification of iris accuracy on the publicly available databases proposed in comparison to the contemporary.

Near infrared light or NIR is not absorbed well by water or blood, which are the main components of biological tissue. For this reason, it can reach a significant depth of optical penetration, thus achieving increased illumination of internal structures. Even if there are some approaches based on near infrared light that allow the analysis of tissue near the skin, there is very little research regarding the 3D reconstruction and visualization of NIR illuminated areas. The current paper presents a review of existing work, analyses the drawbacks and advantages of different methods and proposes new approaches to improve this imaging modality.

The determination of the fruit taste and grade depends on the internal quality of the fruit such as total soluble content, pH, and acidity. This paper investigates the feasibility of a non-destructive method to classify the internal quality of the pineapples using near infrared light and artificial neural network. Five near infrared light emitting diodes (LEDs) were used as the light source to emit near infrared light. A photodiode was used to measure the intensity of the reflected near infrared light from pineapples. The data of the acquired near infrared light were used to classify the internal quality of the pineapple using neural network. The random seed and the hidden neurons of the neural network were optimised to maximise the classification accuracy. Findings indicate that the neural network with seven hidden neurons was capable of achieving 30% misclassification.

This study evaluates the relationship between near infrared light and glucose concentration by means of adaptive linear neuron. Firstly, the design and the development of the proposed glucose measurement device are presented. After that, the experiment design of acquiring sufficient near infrared data for training and testing is described. Next, adaptive linear neuron was trained and validated to predict the glucose concentration based on near infrared light. Findings indicate that the proposed glucose measurement approach by means of near infrared light with different wavelengths (i.e. 850nm, 860nm, 870nm, and 950nm) and adaptive linear neuron was capable of achieving RMSEC of 82.24 mg/dL, RMSEP of 70.04 mg/dL, r p of 0.9066, and r c of 0.9068 for a glucose concentration range of between 20 mg/dL and 600 mg/dL when the learning rate of 0.001 and 207 adaptation cycles were used.

Optical coherence tomography (OCT) using near infrared light is becoming one of the most important modalities for noninvasive assessment of ocular diseases. In many cases, processing OCT image is important for local retinal abnormalities detection. In this paper, we propose a method to identify and quantify cystoids macular edema regions in Spectral Domain OCT (SD-OCT) of the macula. A segmentation algorithm for SD-OCT was developed to detect cystoids within retina. Once the cystoids' borders are detected, a quantitative analysis of liquid in cystoids regions is performed to obtain surface area of fluid in the image. The performance of the proposed segmentation process for the cystoids macular edema was evaluated both qualitatively and quantitatively. Results showed a good agreement between quantitative evaluation and qualitative evaluation done by an ophthalmologist and proved that the process give an acceptable and accurate description of the cystoids regions.

Nowadays, the biometric palm vein is leading trait for person recognition. The biometric is formed on the basis of physiological and behavioral characteristic of human being. The blood vascular structure of each and every individual is unique and distinct. The blood vessel carries oxygenated or deoxygenated blood and found under the skin. The near infrared light illumination visualizes a palm vein pattern. The blood vessel is a superior trait, as it lies beneath a skin that makes it very hard to duplicate, forge or fake. This paper discuss about development of the new recognition technique. The paper also discusses a use of Gabor and canny edge detector to form a basis of vascular structure and thereafter using corner point detection algorithm for efficient extraction of features. The work was focused on the palm vein analysis, its feature extraction and finally identification.

We developed an accurate 3D blood vessel search system for the laparoscopic surgery. In conventional optical systems, artery imaging and detection are difficult because peripheral bio-tissues of the artery disturb, disperse, and refract the light wave propagation, resulting in unclear images. To overcome this problem, we use the near-infrared light, two CMOS camera modules, and a image processing technique along with a stereo method. Unsharp-mask process was employed to sharpen the image quality. The detected artery position showed a good agreement with the true position of pig's gastroepiploic artery specimen, thereby confirming the utility and accuracy of our system.

Venipuncture is a medical practice which is ordinarily performed in hospital. However, it is a difficult procedure as the occurrence of many failure of the puncture and sometimes medical accidents such as nerve damage and blood vessel damage are reported. This is caused by the difficulty of visually identification of the blood vessel. Although the depth information of the blood vessel is also important, the existing system in clinical practice can visualize vessels only by two dimensional images. In this paper, to estimate the three dimensional position of the blood vessel, we propose the system based on refocusing using light field imaging. This method can obtain cross-sectional information of blood vessel emphasized using near infrared light at each depth. We finally confirm the validity of the proposed method by experiments.

We developed unconstraint measurement of vital information using near-infrared light sensor for casual sensing of pulse wave information. This sensor is composed of infrared LED and photodiode for measuring the cyclic change of hemoglobin concentration inside blood vessel. This sensor could measure the pulse wave without constraint of human body. Measured data represented near value to the measured data acquired by commercial photoplethysmographic sensor. We demonstrated the comparisons of measured data by developed sensor with that by commercial sensor, and calculated and compared vascular age and activity balance of autonomous nerve.

Nowadays, in the age of technological development in various areas of life there is a growing interest in non-invasive techniques useful in medical examination. Angiology also called vascular medicine is a medical specialty with interest of diseases and disabilities of the human circulatory system. This domain uses different types of imaging. The acquired images are used for research, diagnostic, therapeutic or educational purposes. Different wavelengths and frequencies are used in the design of medical apparatus. In this paper the usability of near infrared light imaging is discussed and case studies of medical examinations are presented. There is a new approach with range area of applications in angiology.

Diffuse optical imaging (DOI) is a non-invasive technique which measures hemodynamic changes in the tissue with near infrared light, and has been increasingly used to study brain functions. Due to the nature of light propagation in the tissue, the reconstruction problem is severely ill-posed. Sparsityregularization has achieved promising results in recent works for linearized DOI problem. In this paper, we exploit more prior information to improve DOI besides sparsity. Based on the functional specialization of the brain, the in vivo absorption changes caused by specific brain function can be clustered in certain region(s) and not randomly distributed. Thus, a new algorithm is proposed to utilize this prior in reconstruction. Results of numerical simulations and phantom experiments have demonstrated the superiority of the proposed method over the state-of-the-art.

Summarization: The objective of this study is to explore the polarimetric phenomenology of near infrared light interaction with healthy and lung cancer monolayer cells by using efficient polarimetric transmission detection techniques. Preliminary results indicate that enhanced discrimination between normal and different types of lung cancer cell stages can be achieved based on their transmitted intensities and depolarization properties of the cells. Specifically, the sizes of the nuclei of the cancer cells and the nucleus-to-cytoplasmic ratios appear to have potential impact on the detected polarimetric signatures leading to enhanced discrimination of lung cancer cells. Παρουσιάστηκε στο: International Conference on Imaging Systems and Techniques (IST), IEEE

The objective of this study is to explore the phenomenology of near infrared (NIR) light interaction with healthy and early-lung cancer by combining efficient polarimetric backscattering detection techniques with Polarimetric Exploratory Data Analysis (pEDA). Preliminary results indicate that enhanced discrimination signatures can be obtained for certain types of lung cancers.

To assist vascular injection, we have developed a simultaneous observation system for a body surface image and a transillumination image of blood vessels. The system consists of a high-intensity and low-leak light source, near-infrared CMOS camera and a small and light one-eye head mounted display. Using the developed system, we could obtain the transillumination images in all part of the adult forearm with as much as 67 mm thickness. In addition to the superficial veins, we could visualize the arteries in the forearm.

This text based on the scattering principle of lubricating oil to near-infrared light, fully used the computer monitor technology, designed the plan of making use of near-infrared light to monitor automobile lubricating oil, and hereby it to monitor the deteriorated condition of lubricating oil. The experiment has proved that: this kind of technology for monitoring automobile lubricating oil can satisfy the deterioration condition monitor demand of automobile lubricating oil, and can give the instructions of the lubricating oil deterioration degree, so we can decide whether the lubricating oil can continue to use according to it. This method changed the traditional conditions that replace the lubricating oil according to time or the travel course number, it realized replacing lubricating oil according to the quality, thus it make the lubricating oil obtain the reasonable economy service life, and guaranteed the good lubrication condition of vehicles.

In recent years, the incidence of obesity is increasing year by year, and the trend accelerates quickly. Obesity is frequently concomitance with diabetes, fatty liver, blood lipid disorders, hypertension, coronary heart disease and other chronic diseases. So a self-serviced, portable and simple body composition testing apparatus is highly valued. The existing methods have some disadvantages, such as expensive, time-consuming, test condition rigor, suffer some pain or schlep uncomfortable. This paper describes the use of near-infrared technology develop portable fat thickness measurement instrument, to achieve body subcutaneous fat thickness which is a key parameter of body fat content. The method has the advantages such as simple, fast and visual.

We have developed a novel electrooptical method using near infrared light to provide a noninvasive and continuous means of assessing the brain oxygenation and established an animal model in the process for future diagnostic application in humans. The method was evaluated during acute cerebral ischemia and hypoxia.

A very low-power optoelectronic integrated circuit (OEIC) for highly parallel optical receivers is introduced. It is necessary to minimize the power consumption of each optical receiver to enable an array of receivers. An integrated photodiode with low input capacitance takes care of the detection of visible and near infrared light. Rise- and fall times of t/sub r/=470 ps and t/sub f/=421 ps, with an overall (optical and electrical) power consumption of 1.77 mW at a data rate of 500 Mb/s down to a power consumption of 0.66 mW at 40 Mb/s, were achieved. Due to the pin photodiode, a standard 0.6 /spl mu/m BiCMOS process is used, which needs only one minor process modification for the integration of the pin photodiode.

This paper describes the near infrared spectral image measurement system for water absorbency of woven fabrics. This system consists of a pair of near infrared light sources, a series of optical apparatus, a near infrared camera, and an image processor. This paper also describes that the developed measuring system is adequate for testing the time dependent water absorbency of the materials by using the model samples and several woven fabrics. It could be expected that the sensed information obtained by the spectral image could control the quality of the water absorbency more precisely and effectively than the conventional test methods.

A new imaging method using the interaction between the near infrared light and the ultrasonic wave was investigated for application to medical diagnosis. The method was applied to a biological tissue (a dog stomach) including absorbers. The ultrasonic echo pulse from absorbers in the biological tissues shifted due to the illumination of laser diode. The image reconstructed from the shift of ultrasonic echo pulses revealed the shape of the absorber hidden in the biological tissue.

An optical vehicle detector is one of the most important key devices for a Universal Traffic Management System (UTMS) and it has been successfully developed. This newly developed optical vehicle detector uses near infrared light and it detects the vehicles, and is also used to communicate traffic information between the vehicle detector and the vehicle. The most characteristic difference between this newly developed optical vehicle detector and the conventional vehicle detector is not only to supply the traffic information to the driver but also to receive the driver's information including the travel time, vehicle ID, etc., using the optical communication method, and linked to the traffic control center. The operation and features of this new optical vehicle detector for UTMS are described.

The purpose of this work is to develop a near-infrared-light-emitting diode with active materials of monodispersed Si nanocrystallites that are highly compatible with ULSI technology. The monodispersed Si nanocrystallites were synthesized by laser ablation and subsequent size-classification process. The near-infrared emission was sharp and showed a peak above the band-gap region (position: 1.17 eV, width: 0.15 eV); therefore, it presumably originates from spatial quantum confinement effects of the carriers.