• Advances in nano research
• /
• v.11 no.6
• /
• pp.657-665
• /
• 2021

The present work aimed to explore green approach via aqueous leaves extract of Murraya koenigii (ALEMk) for the synthesis of silver nanoparticles (AgNPsMk) in single step. The synthesis process was visualized with a color change and monitored by employing UV/Visible spectroscopy and a clear peak attained at 420 nm confirming the synthesis of AgNPsMk. The possible functional groups present in the extract which participated in the synthesis of AgNPsMk were identified with the help of FTIR spectroscopy. Further characterization using TEM images revealed the spherical shape of AgNPsMk with average particle size of 20 nm displaying well dispersion throughout the solution. Pronounced antioxidant activities of AgNPsMk at increased concentrations observed which evidencing strong radical scavenging ability. Moreover, AgNPsMk exhibited strong antibacterial behavior when tested against bacterial strains of Escherichia coli and Bacillus subtilis. Moving ahead, in vitro cytotoxicity work revealed potent cell viability loss appearing in AU565 and HeLa cancer cell lines on exposure to AgNPsMk at increased concentration. Finally, in vivo assessment carried out inside male Wistar rats indicated non toxic effect on examined liver tissues besides biochemical analysis including bilirubin, alkaline phosphtase (ALP) and serum glutamate pyruvate transaminase (SGPT) which found within the normal range when compared with control. The prior research work profoundly apprises the potential of green synthesized AgNPsMk to play a significant role in biomedical applications and formulations.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.11
• /
• pp.4043-4064
• /
• 2021

Night-time image quality evaluation is an urgent requirement in visual inspection. The lighting environment of night-time results in low brightness, low contrast, loss of detailed information, and colour dissonance of image, which remains a daunting task of delicately evaluating the image quality at night. A new blind quality assessment metric is presented for realistic night-time scenario through a comprehensive consideration of contrast, texture, and colour in this article. To be specific, image blocks' color-gray-difference (CGD) histogram that represents contrast features is computed at first. Next, texture features that are measured by the mean subtracted contrast normalized (MSCN)-weighted local binary pattern (LBP) histogram are calculated. Then statistical features in Lαβ colour space are detected. Finally, the quality prediction model is conducted by the support vector regression (SVR) based on extracted contrast, texture, and colour features. Experiments conducted on NNID, CCRIQ, LIVE-CH, and CID2013 databases indicate that the proposed metric is superior to the compared BIQA metrics.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.23 no.1
• /
• pp.65-70
• /
• 2023

In this paper, we used a deep learning model to detect and segment flame and smoke in real time from fires. To this end, well known U-NET was used to separate and divide the flame and smoke of the fire using multi-class. As a result of learning using the proposed technique, the values of loss error and accuracy are very good at 0.0486 and 0.97996, respectively. The IOU value used in object detection is also very good at 0.849. As a result of predicting fire images that were not used for learning using the learned model, the flame and smoke of fire are well detected and segmented, and smoke color were well distinguished. Proposed method can be used to build fire prediction and detection system.

• Journal of Fashion Business
• /
• v.26 no.5
• /
• pp.62-75
• /
• 2022

The purpose of this study was to analyze the types of aesthetic characteristics and their expression methods in the goth style expressed with the sensibility of an illustrator, using the work of Toon Hertz as an example. As a research method for this purpose, previous studies and books were used to examine the components of fashion illustration, the concept and aesthetic characteristics of goth style, and the world of Toon Hertz's work. In the qualitative studies, Toon Hertz's works were collected and the characteristics of each component were analyzed. As a result of analyzing the aesthetic characteristics, Distortion appeared as the main element of the human body, and the human body was distorted through the method of combining the human body with animals, plants, and other objects. History was mainly expressed through fashion elements. Victorian clothing was predominant, the color was mainly black, and it was characterized by decorations, such as fancy laces, corsets, and shirrings. The screen layout and the object components appeared as the main components of mystery. Sensuality was a major component of the human body, and it emphasized decadent and sensual images of a woman sitting with both legs apart or placing her hands on her legs or chest. Fear was the main component of the human body, and strangeness and fear were created by omitting or removing parts of the body, such as women's arms, legs, hands, or eyes.

• Journal of Biomedical Engineering Research
• /
• v.43 no.6
• /
• pp.441-447
• /
• 2022

In this paper, we propose a pill identification model using engraved text feature and image feature such as shape and color, and compare it with an identification model that does not use engraved text feature to verify the possibility of improving identification performance by improving recognition rate of the engraved text. The data consisted of 100 classes and used 10 images per class. The engraved text feature was acquired through Keras OCR based on deep learning and 1D CNN, and the image feature was acquired through 2D CNN. According to the identification results, the accuracy of the text recognition model was 90%. The accuracy of the comparative model and the proposed model was 91.9% and 97.6%. The accuracy, precision, recall, and F1-score of the proposed model were better than those of the comparative model in terms of statistical significance. As a result, we confirmed that the expansion of the range of feature improved the performance of the identification model.

• Food Science of Animal Resources
• /
• v.42 no.6
• /
• pp.915-927
• /
• 2022

Recently, protein-fortified milk powders are being widely consumed in Korea to prevent sarcopenia, and the demand for high-protein food powders is continuously increasing in the Korean market. However, spray-dried milk proteins have poor flowability and wettability owing to their fine particle sizes and high inter-particle cohesive forces. Fluidized bed agglomeration is widely used to improve the instant properties of food powders. This study investigated the effect of fluidized bed agglomeration on whey protein isolate (WPI)-fortified skim milk powder (SMP) at different SMP/WPI ratios. The fluidized bed process increased the particle size distribution, and agglomerated particles with grape-like structures were observed in the SEM images. As the size increased, the Carr index (CI) and Hausner ratio (HR) values of the agglomerated WPI-fortified SMP particles exhibited excellent flowability (CI: <15) and low cohesiveness (HR: <1.2). In addition, agglomerated WPI-fortified SMP particles exhibited the faster wetting time than the instant criterion (<20 s). As a result, the rheological and physical properties of the WPI-fortified SMP particles were effectively improved by fluidized bed agglomeration. However, the fluidized bed agglomeration process led to a slight change in the color properties. The CIE L^* decreased, and the CIE b^* increased because of the Maillard reaction. The apparent viscosity (η_a,10) and consistency index (K) values of the rehydrated solutions (60 g/180 mL water) increased with the increasing WPI ratio. These results may be useful for formulating protein-fortified milk powder with better instant properties.

• Journal of Broadcast Engineering
• /
• v.28 no.2
• /
• pp.230-237
• /
• 2023

Self-driving is a key technology of the fourth industry and can be applied to various places such as cars, drones, cars, and robots. Among them, localiztion is one of the key technologies for implementing autonomous driving as a technology that identifies the location of objects or users using GPS, sensors, and maps. Locilization can be made using GPS or LIDAR, but it is very expensive and heavy equipment must be mounted, and precise location estimation is difficult for places with radio interference such as underground or tunnels. In this paper, to compensate for this, we proposes an image retrieval using attention module and image segmentation maps using color images acquired with low-cost vision cameras as an input.

• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 1996.06c
• /
• pp.823-833
• /
• 1996

An ultimate purpose of this study is to develop an automatic brown rice quality inspection system using image processing technique. In this study emphasis was put on developing an algorithm for discriminating the brown rice kernels depending on their external quality with a color image processing system equipped with an adaptor for magnifying the input image and optical fiber for oblique illumination. Primarily , geometrical and optical features of sample images were analyzed with unhulled paddy and various brown rice kernel samples such as sound, cracked, green-transparent , green-opaque, colored, white-opaque and brokens. Secondary, an algorithm for discrimination of the rice kernels in static state was developed on the basis of the geometrical and optical parameters screened by a statistical analysis(STEPWISE and DISCRIM Procedure, SAS ver.6). Brown rice samples could be discriminated by the algorithm developed in this study with an accuracy of 90% to 96% for the sound , cracked, colored, broken and unhulled , about 81% for the green-transparent and the white-opaque and about 75% for the green-opaque, respectively. A total computing time required for classification was about 100 seconds/1000 kernels with the PC 80486-DX2, 66MHz.

• International Journal of Computer Science & Network Security
• /
• v.23 no.1
• /
• pp.1-10
• /
• 2023

Open surface water body extraction is gaining popularity in recent years due to its versatile applications. Multiple techniques are used for water detection based on applications. Different applications of Radar as LADAR, Ground-penetrating, synthetic aperture, and sounding radars are used to detect water. Shortwave infrared, thermal, optical, and multi-spectral sensors are widely used to detect water bodies. A stereo camera is another way to detect water and different methods are applied to the images of stereo cameras such as deep learning, machine learning, polarization, color variations, and descriptors are used to segment water and no water areas. The Satellite is also used at a high level to get water imagery and the captured imagery is processed using various methods such as features extraction, thresholding, entropy-based, and machine learning to find water on the surface. In this paper, we have summarized all the available methods to detect water areas. The main focus of this survey is on water detection especially in small patches or in small areas. The second aim of this survey is to detect water hazards for unmanned vehicles and off-sure navigation.

• Journal of the Korea Society of Computer and Information
• /
• v.14 no.12
• /
• pp.89-96
• /
• 2009

A lot of information is contained in an image or a movie rather than in a text, and it is very important thing to extract context from them. In this study, we propose a method to detect an open/closed eye and determine the location of a pupil in an eye image which is extracted from a movie. The image is normalized using transformation into bipolarization with white and black color and horizontalizing, and we measure width and height of an eye. With these information, we can determine the open or closed eye and the location of the pupil. Experiments were done with 52 images of eyes from movies using this method, and we get good results with 98% of correctness in detection of open/closed eyes and 95% in detection of pupil's location.