TELE-OPERATIVE SYSTEM FOR BIOPRODUCTION - REMOTE LOCAL IMAGE PROCESSING FOR OBJECT IDENTIFICATION -
-
- Proceedings of the Korean Society for Agricultural Machinery Conference
- /
- 2000.11b
- /
- pp.300-306
- /
- 2000
This paper introduces a new concept of automation for bio-production with tele-operative system. The proposed system showed practical and feasible way of automation for the volatile bio-production process. Based on the proposition, recognition of the job environment with object identification was performed using computer vision system. A man-machine interactive hybrid decision-making, which utilized a concept of tele-operation was proposed to overcome limitations of the capability of computer in image processing and feature extraction from the complex environment image. Identifying watermelons from the outdoor scene of the cultivation field was selected to realize the proposed concept. Identifying watermelon from the camera image of the outdoor cultivation field is very difficult because of the ambiguity among stems, leaves, shades, and especially fruits covered partly by leaves or stems. The analog signal of the outdoor image was captured and transmitted wireless to the host computer by R.F module. The localized window was formed from the outdoor image by pointing to the touch screen. And then a sequence of algorithms to identify the location and size of the watermelon was performed with the local window image. The effect of the light reflectance of fruits, stems, ground, and leaves were also investigated.
Video surveillance data, which is used for preemptive or post-emptive action against any event or accident, is required for monitoring the location, but is reducing the capacity of the image data by removing intervals for cost reduction and system persistence. Such a video surveillance system is fixed in a certain position and monitors the area only within a limited angle, or monitors only the fixed area without changing the angle. At this time, the video surveillance system that is monitored only within a limited angle shows that the variation object such as the floating population shows different status in the image, and the background of the image maintains a generally constant appearance. The static objects in the image do not need to be stored in all the images, unlike the dynamic objects that must be continuously shot, and occupy a storage space other than the necessary ones. In this paper, we propose a mechanism to analyze the image, store only the small size image for the fixed background, and store it as image data only for variable objects.
This study analyzed the difference between 2D image and 3D virtual clothing images based on stripe arrangement to obtain fundamental data for slim appearance. First, the slimming effect according to the three types of stripe ratio was examined. Subsequently, the slimming effects of seven types of one-piece dress designs according to the stripe location were analyzed. Subjective ranking was evaluated. The width items and radius of curvature were measured for the image's respective parts. Consequently, in 2D image and 3D virtual clothing images, the one with the narrowest stripe ratio was evaluated as the slimmest; however, the conditions for the slimming effect were different. In the seven one-piece dress designs, a difference was apparent in the ranking of the 2D image and 3D virtual clothing images. In the 3D virtual clothing image, arranging the stripes on the entire garment proved inefficient. The stripes were curved according to the curvature of the human body, creating an optical illusion that differed from that of the 2D image.
Conceptualization of store image have been suggested in the past by many marketing scholars. The dominant perspective about store image is treated as the results of a multi-attribute model. Store image is expressed as a function of the salient attributes of a particular store that are evaluated. Though, there is a little confusions about what elements compose the store image, most scholars agree that merchandise, service, atmosphere, physical facilities, comfort, and location are generally accepted elements as store image. A considerable researches support that shopping can provide both hedonic and utilitarian value. Hedonic shopping value reflects the value received from fantasy and emotive aspects of shopping experience, while utilitarian shopping value reflects the acquisition of products. These two types of shopping value can affect shopping satisfaction. This study examines the relationships among stores images(store atmosphere, salespeople services, facilities, product assortment, and store location), shopping values(utilitarian shopping value and hedonic shopping value), and shopping satisfaction based on discount stores (E-Mart, Home plus, and Lotte Mart). The author hypothesized that five store image components affect shopping values, and these shopping values affect shopping satisfaction. The author focused on the roles of perceived retail crowding between these relationships. Specifically, the author hypothesized that perceived retailing crowding moderated the relationship between shopping values and shopping satisfaction. The author also hypothesized the direct effect of perceived retail crowding on shopping satisfaction. Finally, the author hypothesized that five store image components affect directly shopping satisfaction. Research model is presented in
Gwanghwamun Gate of Gyeongbokgung Palace was dismantled and relocated during the Japanese colonial period, destroyed during the Korean War, reconstructed with reinforced concrete in 1968, and finally erected at its present location in 2010. A pair of Haechi statues located in front of Gwanghwamun was dismantled and relocated several times, and the statues have yet to be returned precisely to their original positions. This study assesses the historical accuracy of their current placement under the Gwanghwamun Square Restructuring Project of the Seoul Metropolitan Government and the Cultural Heritage Administration based on archival photos from the early 1900s, and proposes a method to estimate the original positions of the Haechi through image analysis of contemporary photographs and recent digital camera photos. We estimated the original position of the Haechi before the Japanese colonial period by identifying the shooting location of the archival photo and reproducing contemporary photographs by calculating the angle and distance to the Haechi from the shooting location. The leftmost and rightmost Haechi were originally located about 9.6 m to the east and 7.4 m to the north and about 1.9 m to the west and 8.0 m to the north, respectively, of their current location indicators. As the first attempt to determine the original location of a building and its accessories using archival photos, this study launches a new scientific methodology for the restoration of cultural properties.
Microscopic imaging system often requires the algorithm to adjust location of camera lenses automatically in machine level. An effort to detect the best focal point is naturally interpreted as a mathematical inverse problem [1]. Following Wiener's point of view [2], we interpret the focus level of images as the quantified factor appeared in image degradation model: g =
In this paper, we propose an approach to identify the driving environment for intelligent highway vehicles by means of image processing and computer vision techniques. The proposed approach mainly consists of two consecutive computational steps. The first step is the lane marking detection, which is used to identify the location of the host vehicle and road geometry. In this step, related standard image processing techniques are adapted for lane-related information. In the second step, by using the output from the first step, a four-stage algorithm for vehicle detection is proposed to provide information on the relative position and speed between the host vehicle and each preceding vehicle. The proposed approach has been validated in several real-world scenarios. Herein, experimental results indicate low false alarm and low false dismissal and have demonstrated the robustness of the proposed detection approach.
Elshayal
Grey-level statistical models have been widely used in many applications for object location and identification. However, conventional models yield some problems in model refinement when training images are not properly aligned, and have difficulties for real-time recognition of arbitrarily rotated models. This paper presents improved grey-level statistical models that align training images using image or feature matching to overcome problems in model refinement of conventional models, and that enable real-time recognition of arbitrarily rotated objects using efficient hierarchical search methods. Edges or features extracted from a mean training image are used for accurate alignment of models in the search image. On the aligned position and orientation, fitness measure based on grey-level statistical models is computed for object recognition. It is demonstrated in various experiments in PCB inspection that proposed methods are superior to conventional methods in recognition accuracy and speed.
An active contour model, Snake, was developed as a useful segmenting and tracking tool lot rigid or non-rigid (i.e. deformable) objects by Kass in 1987 In this research, Snake is newly designed to cover this large moving case. Image flow energy is proposed to give Snake the motion information of the target object. By this image flow energy Snake's nodes can move uniformly along the direction of the target motion in spite of the existences of local minima. Furthermore, when the motion is too large to apply image flow energy to tracking, a jump mode is proposed for solving the problem. The vector used to make Snake's nodes jump to the new location can be obtained by processing the image flow. The effectiveness of the proposed Snake is confirmed by some simulations.
. To test model and hypotheses, data were collected from 114 consumers located mid-size city in local area. The author employs PLS methodology (SmartPLS 2.0) to test hypotheses. Data analysis results indicate that among five store images salespeople services, and store location affect utilitarian shopping value. Store atmosphere, salespeople services, and store location affect hedonic shopping value. Two shopping values affect shopping satisfaction. Hedonic shopping value affect more shopping satisfaction than utilitarian shopping value. Data analysis results is presented in . The author examines the moderating effects of perceived retail crowding between shopping values and shopping satisfaction. Results indicate that there are no moderating effects between shopping values and shopping satisfaction. Moderating effects of perceived retail crowding between utilitarian shopping value and shopping satisfaction are presented in
. Moderating effects of perceived retail crowding between hedonic shopping value and shopping satisfaction is presented in
. The author analyzed the relationship between perceived retail crowding and shopping satisfaction using WarpPLS 3.0 which can analyze the non-linear relationship. Result indicates that perceived retail crowding affects directly shopping satisfaction and there is a non-linear relationship between them. Among five store image components, store atmosphere and salespeople services affect directly shopping satisfaction. The author describes about the managerial implications, limitations, and future research issues.
Estimation of the Original Location of Haechi (Haetae) Statues in Front of Gwanghwamun Gate Using Archival Photos from Early 1900s and Newly Taken Photos by Image Analysis
(1900년대 초반의 기록사진과 디지털 카메라 사진분석을 활용한 광화문 앞 해치상의 원위치 추정)
APPLICATION OF HISTOGRAM OUTLIER ANALYSIS ON THE IMAGE DEGRADATION MODEL FOR BEST FOCAL POINT SELECTION
IMAGE PROCESSING TECHNIQUES FOR LANE-RELATED INFORMATION EXTRACTION AND MULTI-VEHICLE DETECTION IN INTELLIGENT HIGHWAY VEHICLES
A GIS, GPS, Database, Internet GIS
Improved Statistical Grey-Level Models for PCB Inspection
(PCB 검사를 위한 개선된 통계적 그레이레벨 모델)
Visual Tracking Using Snake Algorithm Based on Optical Flow Information
이메일무단수집거부
이용약관
제 1 장 총칙
제 2 장 이용계약의 체결
제 3 장 계약 당사자의 의무
제 4 장 서비스의 이용
제 5 장 계약 해지 및 이용 제한
제 6 장 손해배상 및 기타사항
Detail Search
Image Search
(β)