• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4903-4929
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• 2018

In this study, a fully automatic pose and expression invariant 3D face alignment algorithm is proposed to handle frontal and profile face images which is based on a two pass course to fine alignment strategy. The first pass of the algorithm coarsely aligns the face images to an intrinsic coordinate system (ICS) through a single 3D rotation and the second pass aligns them at fine level using a minimum nose tip-scanner distance (MNSD) approach. For facial recognition, multi-view faces are synthesized to exploit real 3D information and test the efficacy of the proposed system. Due to optimal separating hyper plane (OSH), Support Vector Machine (SVM) is employed in multi-view face verification (FV) task. In addition, a multi stage unified classifier based face identification (FI) algorithm is employed which combines results from seven base classifiers, two parallel face recognition algorithms and an exponential rank combiner, all in a hierarchical manner. The performance figures of the proposed methodology are corroborated by extensive experiments performed on four benchmark datasets: GavabDB, Bosphorus, UMB-DB and FRGC v2.0. Results show mark improvement in alignment accuracy and recognition rates. Moreover, a computational complexity analysis has been carried out for the proposed algorithm which reveals its superiority in terms of computational efficiency as well.

• Journal of IKEEE
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• v.28 no.3
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• pp.469-473
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• 2024

In this paper proposes a study on the development of a multi-camera inline inspection system using machine vision for quality inspection of pharmaceutical containers. The proposed technique captures the pharmaceutical containers from multiple angles using several cameras, allowing for more accurate quality assessment. Based on the captured data, the system inspects the dimensions and defects of the containers and, upon detecting defects, notifies the user and automatically removes the defective containers, thereby enhancing inspection efficiency. The development of the multi-camera inline inspection system using machine vision is divided into four stages. First, the design and production of a control unit that fixes or rotates the containers via suction. Second, the design and production of the main system body that moves, captures, and ejects defective products. Third, the design and development of control logic for the embedded board that controls the entire system. Finally, the design and development of a user interface (GUI) that detects defects in the pharmaceutical containers using image processing of the captured images. The system's performance was evaluated through experiments conducted by a certified testing agency. The results showed that the dimensional measurement error range of the pharmaceutical containers was between -0.30 to 0.28 mm (outer diameter) and -0.11 to 0.57 mm (overall length), which is superior to the global standard of 1 mm. The system's operational stability was measured at 100%, demonstrating its reliability. Therefore, the efficacy of the proposed multi-camera inline inspection system using machine vision for the quality inspection of pharmaceutical containers has been validated.

• Journal of Mechanical Science and Technology
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• v.17 no.10
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• pp.1411-1422
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• 2003

The detection of free spaces between obstacles in a scene is a prerequisite for navigation of a mobile robot. Especially for stereo vision-based navigation, the problem of correspondence between two images is well known to be of crucial importance. This paper describes multi-range approach of area-based stereo matching for grid mapping and visual navigation in uncertain environment. Camera calibration parameters are optimized by evolutionary algorithm for successful stereo matching. To obtain reliable disparity information from both images, stereo images are to be decomposed into three pairs of images with different resolution based on measurement of disparities. The advantage of multi-range approach is that we can get more reliable disparity in each defined range because disparities from high resolution image are used for farther object a while disparities from low resolution images are used for close objects. The reliable disparity map is combined through post-processing for rejecting incorrect disparity information from each disparity map. The real distance from a disparity image is converted into an occupancy grid representation of a mobile robot. We have investigated the possibility of multi-range approach for the detection of obstacles and visual mapping through various experiments.

• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.2
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• pp.127-136
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• 2016

The camera based object detection systems should satisfy the recognition performance as well as real-time constraints. Particularly, in safety-critical systems such as Autonomous Emergency Braking (AEB), the real-time constraints significantly affects the system performance. Recently, multi-core processors and system-on-chip technologies are widely used to accelerate the object detection algorithm by distributing computational loads. However, due to the advanced hardware, the complexity of system architecture is increased even though additional hardwares improve the real-time performance. The increased complexity also cause difficulty in migration of existing algorithms and development of new algorithms. In this paper, to improve real-time performance and design complexity, a task scheduling strategy is proposed for visual object tracking systems. The real-time performance of the vision algorithm is increased by applying pipelining to task scheduling in a multi-core processor. Finally, the proposed task scheduling algorithm is applied to crosswalk detection and tracking system to prove the effectiveness of the proposed strategy.

• Journal of Broadcast Engineering
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• v.20 no.6
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• pp.963-966
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• 2015

This paper introduces a programmable multi-format video decoder(MFD) to support HEVC(High Efficiency Video Coding) standard and for other video coding standards. The goal of the proposed MFD is the high-end FHD(Full High Definition) video decoder needed for a DTV(Digital Tele-Vision) SoC(System on Chip). The proposed platform consists of a hybrid architecture that is comprised of reconfigurable processors and flexible hardware accelerators to support the massive computational load and various kinds of video coding standards. The experimental results show that the proposed architecture is operating at a 300MHz clock that is capable of decoding HEVC bit-stream of FHD 30 frames per second.

• Journal of the Microelectronics and Packaging Society
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• v.26 no.2
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• pp.59-64
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• 2019

In this paper, we introduced a near-infrared multi-channel fluorescence imaging system and analyzed the effects of measurements variables such as exposure time, working distance and intensity of excitation light. Fluorescence signal is increased as exposure time becomes longer, excitation light intensity increases or working distance becomes smaller. Furthermore, the proper composition of optical filters and precise packaging of the imaging modules prevent the increase of background signal. Thus, we confirmed an increase in SBR. Based on the result of this research, we proposed a method to use a multi-channel fluorescence imaging system.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.10
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• pp.993-998
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• 2007

To verify the 2D or 3D positioning accuracy of a multi-axes stage is not easy, particularly, in the case the moving path of the stage is not linear. This paper is a study on a measuring method for the curved path accurately. A machine vision technique is used to trace the moving path of two-axes stage. To improve the accuracy of machine vision, a zoom lens is used for the 2D micro moving path. The accuracy of this method depends of the CCD resolution and array align accuracy with the zoom lens system. Also, a further study for software algorithm is required to increase the tracing speed. This technique will be useful to trace a small object in the 2D micro path in real-time accurately.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.2 s.95
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• pp.68-73
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• 1999

Generally, most of machining processes are done according to the dimention of the draft made by CAD. However, there are many cases that a sample is given without the draft because of the simplicity of the shape in the machining of 2D objects. To cut the same shape as the given sample, this paper proposes the method to extract the geometric information about a large sample using the robot vision and to draw the demensional draft for the machining. Because the resolution of one frame in the vision system is too low, it is necessary to set up a camera according to the desired resolution and to capture the image moving along the contour. And the overall outline can be compounded of the sequentially captured images. In the experiment, we compared the product after the cutting with the original sample and found that the size of two objects was coincided within the allowed error bound.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2780-2782
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• 2005

In this paper, we present a mobile robot localization solution by using a Ubiquitous Vision System (UVS). The collective information gathered by multiple cameras that are strategically placed has many advantages. For example, aggregation of information from multiple viewpoints reduces the uncertainty about the robots' positions. We construct UVS as a multi-agent system by regarding each vision sensor as one vision agent (VA). Each VA performs target segmentation by color and motion information as well as visual tracking for multiple objects. Our modified identified contractnet (ICN) protocol is used for communication between VAs to coordinate multitask. This protocol raises scalability and modularity of thesystem because of independent number of VAs and needless calibration. Furthermore, the handover between VAs by using ICN is seamless. Experimental results show the robustness of the solution with respect to a widespread area. The performance in indoor environments shows the feasibility of the proposed solution in real-time.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.5
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• pp.14-23
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• 2007

Welding fabrication invariantly involves three district sequential steps: preparation, actual process execution and post-weld inspection. One of the major problems in automating these steps and developing autonomous welding system is the lack of proper sensing strategies. Conventionally, machine vision is used in robotic arc welding only for the correction of pre-taught welding paths in single pass. However, in this paper, multipass tracking more than single pass tracking is performed by conventional seam tracking algorithm and developed one. And tracking performances of two algorithm are compared in multipass tracking. As the result, tracking performance in multi-pass welding shows superior conventional seam tracking algorithm to developed one.