• Journal of Advanced Marine Engineering and Technology
• /
• v.18 no.4
• /
• pp.62-68
• /
• 1994

Recently, the trends toward reduction in size and weight of industrial products increased the application of micro hole for manufacturing gadgets of high precision and gave rise to a great deal of interest for micro hole drilling M/C. Quite a few research work is performed on micro drilling on domestic basis compared with the tendency of analyzing cutting mechanism, adaptive control, monitoring of generally available drills of diameter greater than 1mm. This study adresses the design, manufacturing and controlling a micro hole drilling M/C with the overload detection instrument and the step feed mechanism. Controlling and monitoring of the drilling process are acomplished on PC basis for more user interfaces and effectiveness. The test machine of the results of this research shows a good foundation for extending further micro hole machining technique.

• International Journal of Computer Science & Network Security
• /
• v.22 no.9
• /
• pp.280-286
• /
• 2022

Facial recognition system is a biometric manipulation. Its applicability is simpler, and its work range is broader than fingerprints, iris scans, signatures, etc. The system utilizes two technologies, such as face detection and recognition. This study aims to develop a facial recognition system to recognize person's faces. Facial recognition system can map facial characteristics from photos or videos and compare the information with a given facial database to find a match, which helps identify a face. The proposed system can assist in face recognition. The developed system records several images, processes recorded images, checks for any match in the database, and returns the result. The developed technology can recognize multiple faces in live recordings.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.10
• /
• pp.203-208
• /
• 2019

Digital watermarking was developed to protect copyright by discouraging the illegal copying of digital content. On the other hand, recently, watermarking has also been used to verify the integrity of digital content, such as medical images, and detect illegal manipulation or distortion locations. Watermarking should be tenacious so as to protect copyright from illegal copying and should remain firm to the content through a range of attacks, such as distortion or filtering. At the same time, however, it should be removed easily even in a slight transformation of the material to verify the integrity. Therefore, this paper proposes a watermarking technique that easily checks and verifies the deformation or manipulation of digital images. In the proposed method, the entire image was examined in $16{\times}16$ blocks to check for deformation of the image. When deformation was detected, further inspection proceeded in $4{\times}4$ blocks and the location where deformation occurred was identified.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.19 no.1
• /
• pp.1-8
• /
• 2024

Robotic arms have been widely utilized in various labor-intensive industries such as manufacturing, agriculture, and food services, contributing to increasing productivity. In the development of industrial robotic arms, camera sensors have many advantages due to their cost-effectiveness and small sizes. However, estimating object positions is a challenging problem, and it critically affects to the robustness of object manipulation functions. This paper proposes a method for estimating the 3D positions of objects, and it is applied to a pick-and-place task. A deep learning model is utilized to detect 2D bounding boxes in the image plane, and the pinhole camera model is employed to compute the object positions. To improve the robustness of measuring the 3D positions of objects, we analyze the effect of lens distortion and introduce a false positive filtering process. Experiments were conducted on a real-world scenario for moving medicine bottles by using a camera-based manipulator. Experimental results demonstrated that the distortion removal and false positive filtering are effective to improve the position estimation precision and the manipulation success rate.

• Journal of Microbiology and Biotechnology
• /
• v.17 no.1
• /
• pp.5-14
• /
• 2007

Nanotechnology is the creation and utilization of materials, devices, and systems through the control of matter on the nanometer. The technology has been applied to biodevices such as bioelectronics and biochips to improve their performances. Nanoparticles, such as gold (Au) nanoparticles, are the most widely used of the various other nanotechnologies for manipulation at the nanoscale as well as nanobiosensors. The immobilization of biomolecules is playing an increasingly important role in the development of biodevices with high performance. Nanopatteming technology, which is able to increase the density of chip arrays, offers several advantages, including cost lowering, simultaneous multicomponent detection, and the efficiency increase of biochemical reactions. A microftuidic system incorporated with control of nanoliter of fluids is also one of the main applications of nanotechnologies. This can be widely utilized in the various fields because it can reduce detection time due to tiny amounts of fluids, increase signal-to-noise ratio by nanoparticles in channel, and detect multi-targets simultaneously in one chamber. This article reviews nanotechnologies such as the application of nanoparticles for the detection of biomolecules, the immobilization of biomolecules at nanoscale, nanopatterning technologies, and the microfluidic system for molecular diagnosis.

• Journal of IKEEE
• /
• v.22 no.2
• /
• pp.227-232
• /
• 2018

Nowadays, image manipulation is enormously popular and easier than ever with tons of convenient images editing tools. After several simple operations, users can get visually attractive images which easily trick viewers. In this paper, we propose a fast algorithm which can detect the image splicing using the Markov features. The proposed algorithm reduces the computational complexity by removing unnecessary Markov features which are not used in the image splicing detection process. The performance of the proposed algorithm is evaluated using a famous image splicing dataset which is publicly available. The experimental results show that the proposed technique outperforms the state-of-the-art splicing detection methods.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.4 no.4
• /
• pp.618-632
• /
• 2010

This paper presents a novel approach to control the augmented reality (AR) objects robustly in a marker-less AR system by fingertip tracking and hand pattern recognition. It is known that one of the promising ways to develop a marker-less AR system is using human's body such as hand or face for replacing traditional fiducial markers. This paper introduces a real-time method to manipulate the overlaid virtual objects dynamically in a marker-less AR system using both hands with a single camera. The left bare hand is considered as a virtual marker in the marker-less AR system and the right hand is used as a hand mouse. To build the marker-less system, we utilize a skin-color model for hand shape detection and curvature-based fingertip detection from an input video image. Using the detected fingertips the camera pose are estimated to overlay virtual objects on the hand coordinate system. In order to manipulate the virtual objects rendered on the marker-less AR system dynamically, a vision-based hand control interface, which exploits the fingertip tracking for the movement of the objects and pattern matching for the hand command initiation, is developed. From the experiments, we can prove that the proposed and developed system can control the objects dynamically in a convenient fashion.

• Journal of Internet Computing and Services
• /
• v.4 no.4
• /
• pp.27-34
• /
• 2003

Digital image manipulation software is now readily available on personal computers. It is therefore very simple to tamper with any image and make it available to others. Therefore. copyright protection of digital contents and insurance of digital image integrity become major issues. In this paper, we propose a hybrid watermarking method to identify locations of tampered region as well as copyright. Our proposed algorithms embed the PN-sequence into low frequency sub-band of the wavelet transform domain and it doesn't need the original image in extraction procedure. The experimental results show good robustness against any signal processing with tamper detection on still image.

• Journal of IKEEE
• /
• v.25 no.2
• /
• pp.285-290
• /
• 2021

The existing aiming inspection use foreign-made aiming inspection equipment. However, the quantity is insufficient and the difficult to maintain. So it takes a lot of time to inspect the target. This system can reduces the time of aiming inspection and be maintained and distributed smoothly because it is a domestic product. In this paper, we develop a system that can detect targets and monitor shooting results through a target detection deep learning model. The system is capable of real-time detection of targets and has significantly increased the identification rate through several preprocessing of distant targets. In addition, a graphical user interface is configured to facilitate user camera manipulation and storage and management of training result data. Therefore the system can replace the currently used aiming inspection equipment and non-fire training.

• International Journal of Computer Science & Network Security
• /
• v.22 no.8
• /
• pp.242-248
• /
• 2022

The article presents the analysis of modern methods of automatic comparison of original and unoriginal text to detect textual plagiarism. The study covers two types of plagiarism - literal, when plagiarists directly make exact copying of the text without changing anything, and intelligent, using more sophisticated techniques, which are harder to detect due to the text manipulation, like words and signs replacement. Standard techniques related to extrinsic detection are string-based, vector space and semantic-based. The first, most common and most successful target models for detecting literal plagiarism - N-gram and Vector Space are analyzed, and their advantages and disadvantages are evaluated. The most effective target models that allow detecting intelligent plagiarism, particularly identifying paraphrases by measuring the semantic similarity of short components of the text, are investigated. Models using neural network architecture and based on natural language sentence matching approaches such as Densely Interactive Inference Network (DIIN), Bilateral Multi-Perspective Matching (BiMPM) and Bidirectional Encoder Representations from Transformers (BERT) and its family of models are considered. The progress in improving plagiarism detection systems, techniques and related models is summarized. Relevant and urgent problems that remain unresolved in detecting intelligent plagiarism - effective recognition of unoriginal ideas and qualitatively paraphrased text - are outlined.