• Title/Summary/Keyword: visual estimation method

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High-Quality Coarse-to-Fine Fruit Detector for Harvesting Robot in Open Environment

  • Zhang, Li;Ren, YanZhao;Tao, Sha;Jia, Jingdun;Gao, Wanlin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.2
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    • pp.421-441
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    • 2021
  • Fruit detection in orchards is one of the most crucial tasks for designing the visual system of an automated harvesting robot. It is the first and foremost tool employed for tasks such as sorting, grading, harvesting, disease control, and yield estimation, etc. Efficient visual systems are crucial for designing an automated robot. However, conventional fruit detection methods always a trade-off with accuracy, real-time response, and extensibility. Therefore, an improved method is proposed based on coarse-to-fine multitask cascaded convolutional networks (MTCNN) with three aspects to enable the practical application. First, the architecture of Fruit-MTCNN was improved to increase its power to discriminate between objects and their backgrounds. Then, with a few manual labels and operations, synthetic images and labels were generated to increase the diversity and the number of image samples. Further, through the online hard example mining (OHEM) strategy during training, the detector retrained hard examples. Finally, the improved detector was tested for its performance that proved superior in predicted accuracy and retaining good performances on portability with the low time cost. Based on performance, it was concluded that the detector could be applied practically in the actual orchard environment.

A Macroblock-Layer Rate Control with Adaptive Quantization Parameter Decision and Header Bits Length Estimation (적응적 양자화 파라미터 결정과 헤더 비트량 예측을 통한 매크로블록 단위 비트율 제어)

  • Kim, Se-Ho;Suh, Jae-Won
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.2C
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    • pp.200-208
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    • 2009
  • A macroblock layer rate control for H.264/AVC has the problem that allocated target bits for current frame occasionally are exhausted too fast due to inadequate quantization parameter assignment. In this case, the maximum permissible quantization parameter is used to encode for remaining macroblocks and it leads to degradation of the visual quality. In addition, the header bits length estimation algorithm used for quantization parameter assignment takes the average header bits length for the encoded macroblocks of the previous frame and the current frame. Therefore, it generates a big mismatch between the actually generated header bits length and the estimated header bits length. In this paper, we propose adaptive quantization parameter decision method to prevent early exhausting target bits during encoding the current frame by considering the number of macroblocks that have negative targets bits in previous frame and the improved header bits length estimation scheme for accurate quantization parameter decision.

The Design of Adaptive Quantizer to Improve Image Quality of the H.263 (H.263의 화질 개선을 위한 적응 양자화기 설계)

  • 신경철;이광형
    • The Journal of the Acoustical Society of Korea
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    • v.18 no.6
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    • pp.77-83
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    • 1999
  • H.263 is an international standard of ITU-T that can makes the service such as video phone, video conference in the transmission line less than 64Kbps. This recommendation draft has used motion estimation/compensation, transform coding and quantizing methods. TMN5 used for the performance estimation of H.263 has fundamentally used DCT in transform coding method and presented quantizer for quantizing the DCT transform coefficient. This paper is presenting adaptive quantizer effectively able to quantize DCT coefficient considering the human visual sensitivity while the structure of TMN5 is maintaining. As quantizer that proposed DCT-based H.263 could make transmit more frame than TMN5 in a same transfer speed, it could lower the frame drop effect. And the luminance signal appeared the difference of -0.3 ~ +0.7dB in the average PSNR for the estimation of objective image quality and the chrominance signal appeared the improvement in about 1.5dB in comparision with TMN5. As a result it can attain the better image quality compared to TMN5 in the estimation of subjective image quality.

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Development of an Image Processing System for the Large Size High Resolution Satellite Images (대용량 고해상 위성영상처리 시스템 개발)

  • 김경옥;양영규;안충현
    • Korean Journal of Remote Sensing
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    • v.14 no.4
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    • pp.376-391
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    • 1998
  • Images from satellites will have 1 to 3 meter ground resolution and will be very useful for analyzing current status of earth surface. An image processing system named GeoWatch with more intelligent image processing algorithms has been designed and implemented to support the detailed analysis of the land surface using high-resolution satellite imagery. The GeoWatch is a valuable tool for satellite image processing such as digitizing, geometric correction using ground control points, interactive enhancement, various transforms, arithmetic operations, calculating vegetation indices. It can be used for investigating various facts such as the change detection, land cover classification, capacity estimation of the industrial complex, urban information extraction, etc. using more intelligent analysis method with a variety of visual techniques. The strong points of this system are flexible algorithm-save-method for efficient handling of large size images (e.g. full scenes), automatic menu generation and powerful visual programming environment. Most of the existing image processing systems use general graphic user interfaces. In this paper we adopted visual program language for remotely sensed image processing for its powerful programmability and ease of use. This system is an integrated raster/vector analysis system and equipped with many useful functions such as vector overlay, flight simulation, 3D display, and object modeling techniques, etc. In addition to the modules for image and digital signal processing, the system provides many other utilities such as a toolbox and an interactive image editor. This paper also presents several cases of image analysis methods with AI (Artificial Intelligent) technique and design concept for visual programming environment.

Diagnosis of the Rice Lodging for the UAV Image using Vision Transformer (Vision Transformer를 이용한 UAV 영상의 벼 도복 영역 진단)

  • Hyunjung Myung;Seojeong Kim;Kangin Choi;Donghoon Kim;Gwanghyeong Lee;Hvung geun Ahn;Sunghwan Jeong;Bvoungiun Kim
    • Smart Media Journal
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    • v.12 no.9
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    • pp.28-37
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    • 2023
  • The main factor affecting the decline in rice yield is damage caused by localized heavy rains or typhoons. The method of analyzing the rice lodging area is difficult to obtain objective results based on visual inspection and judgment based on field surveys visiting the affected area. it requires a lot of time and money. In this paper, we propose the method of estimation and diagnosis for rice lodging areas using a Vision Transformer-based Segformer for RGB images, which are captured by unmanned aerial vehicles. The proposed method estimates the lodging, normal, and background area using the Segformer model, and the lodging rate is diagnosed through the rice field inspection criteria in the seed industry Act. The diagnosis result can be used to find the distribution of the rice lodging areas, to show the trend of lodging, and to use the quality management of certified seed in government. The proposed method of rice lodging area estimation shows 98.33% of mean accuracy and 96.79% of mIoU.

Heave Motion Estimation of a Ship Deck for Shipboard Landing of a VTOL UAV (수직이착륙 무인기 함상 착륙점의 상하 운동 추정)

  • Cho, Am;Yoo, Changsun;Kang, Youngshin;Park, Bumjin
    • Journal of Aerospace System Engineering
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    • v.8 no.3
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    • pp.14-19
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    • 2014
  • When a helicopter lands on a ship deck in high sea states, one of main difficulties is the ship motion by sea wave, In case of a manned helicopter, a pilot lands a helicopter on the deck during quiescent period of ship motion, which is perceived from different visual cues around landing spot. The capability to predict this quiescent period is very important especially for shipboard recovery of VTOL UAV in harsh environments. This paper describes how to predict heave motion of a ship for shipboard landing of a VTOL UAV. For simulation, ship motion by sea wave was generated using a 4,000 ton class US destroyer model. Heave motion of ship deck was predicted by applying auto-regression method to generated time series data of ship motion.

An Estimation of Deformation for Composites by DIC (DIC에 의한 복합재료 변형측정)

  • Kwon, Oh-Heon;Kang, Ji-Woong
    • Journal of Power System Engineering
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    • v.18 no.4
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    • pp.78-84
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    • 2014
  • The estimation of deformation and strain for the twill-weave carbon fiber reinforced plastic composite(CFRP) during the test with a digital image correlation system were implemented experimentally. The carbon fiber reinforced plastic composites have been developed as the edge technology materials. The plain, twill and satin weave types are commonly used for the CFRP composites. Thus, it is essential to find the deformation characteristics for those types of CFRP more easily. Especially the DIC method can express the visual strain distributions at the full range of the interested areas in the structures. In this study, the mechanical properties of twill-weave CFRP composite and the variation of strains in a full field of the specimen were estimated. The experiments were performed under a tensile loading and 3-point bending test with strain gages. Futhermore the DIC deformation results were estimated for the comparison. The results showed the deformation and strain contours visually well in all region of the interested areas and so usefulness for the safety control of the structures.

Vision-based Camera Localization using DEM and Mountain Image (DEM과 산영상을 이용한 비전기반 카메라 위치인식)

  • Cha Jeong-Hee
    • Journal of the Korea Society of Computer and Information
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    • v.10 no.6 s.38
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    • pp.177-186
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    • 2005
  • In this Paper. we propose vision-based camera localization technique using 3D information which is created by mapping of DEM and mountain image. Typically, image features for localization have drawbacks, it is variable to camera viewpoint and after time information quantify increases . In this paper, we extract invariance features of geometry which is irrelevant to camera viewpoint and estimate camera extrinsic Parameter through accurate corresponding Points matching by Proposed similarity evaluation function and Graham search method we also propose 3D information creation method by using graphic theory and visual clues, The Proposed method has the three following stages; point features invariance vector extraction, 3D information creation, camera extrinsic Parameter estimation. In the experiments, we compare and analyse the proposed method with existing methods to demonstrate the superiority of the proposed methods.

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Real-time Monocular Camera Pose Estimation using a Particle Filiter Intergrated with UKF (UKF와 연동된 입자필터를 이용한 실시간 단안시 카메라 추적 기법)

  • Seok-Han Lee
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.16 no.5
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    • pp.315-324
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    • 2023
  • In this paper, we propose a real-time pose estimation method for a monocular camera using a particle filter integrated with UKF (unscented Kalman filter). While conventional camera tracking techniques combine camera images with data from additional devices such as gyroscopes and accelerometers, the proposed method aims to use only two-dimensional visual information from the camera without additional sensors. This leads to a significant simplification in the hardware configuration. The proposed approach is based on a particle filter integrated with UKF. The pose of the camera is estimated using UKF, which is defined individually for each particle. Statistics regarding the camera state are derived from all particles of the particle filter, from which the real-time camera pose information is computed. The proposed method demonstrates robust tracking, even in the case of rapid camera shakes and severe scene occlusions. The experiments show that our method remains robust even when most of the feature points in the image are obscured. In addition, we verify that when the number of particles is 35, the processing time per frame is approximately 25ms, which confirms that there are no issues with real-time processing.

Steady-State Visual Evoked Potential (SSVEP)-based Rehabilitation Training System with Functional Electrical Stimulation (안정상태 시각유발전위 기반의 기능적 전기자극 재활훈련 시스템)

  • Sohn, R.H.;Son, J.;Hwang, H.J.;Im, C.H.;Kim, Y.H.
    • Journal of Biomedical Engineering Research
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    • v.31 no.5
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    • pp.359-364
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    • 2010
  • The purpose of the brain-computer (machine) interface (BCI or BMI) is to provide a method for people with damaged sensory and motor functions to use their brain to control artificial devices and restore lost ability via the devices. Functional electrical stimulation (FES) is a method of applying low level electrical currents to the body to restore or to improve motor function. The purpose of this study was to develop a SSVEP-based BCI rehabilitation training system with FES for spinal cord injured individuals. Six electrodes were attached on the subjects' scalp ($PO_Z$, $PO_3$, $PO_4$, $O_z$, $O_1$ and $O_2$) according to the extended international 10-20 system, and reference electrodes placed at A1 and A2. EEG signals were recorded at the sampling rate of 256Hz with 10-bit resolution using a BIOPAC system. Fast Fourier transform(FFT) based spectrum estimation method was applied to control the rehabilitation system. FES control signals were digitized and transferred from PC to the microcontroller using Bluetooth communication. This study showed that a rehabilitation training system based on BCI technique could make successfully muscle movements, inducing electrical stimulation of forearm muscles in healthy volunteers.