• The Research Journal of the Costume Culture
• /
• v.15 no.6
• /
• pp.996-1007
• /
• 2007

This study was focused on recognitive reaction. The purposes of this study was to analyze the fashion brands through correlation analysis between top of mind, recall, recognition, impact index and consumer behavior, and to identify the graveyard brand, niche brand and core brand. 33 questions about 20 fashion brands were asked to 442 males and females from the middle school students to age of 40. Data were analyzed mean, standard deviation, frequency, and correlation by using SPSS 12.0. The results were as follows: 1. Top of mind, recall and recognition affected recognizing the brands and including evoked setting, but it didn't lead the customer to purchase the brand. 2. Although top of the mind and recall are high, the percentage of purchasing the brand is relatively low if a consumer doesn't own the brand. 3. Brands 'B', 'L', 'PF', 'D' and 'BM' were represented as niche Brands which had high recognition and memory. 4. Brands 'TB', 'I', 'EN', 'ML', 'E' could be Graveyard brands that need special management. 5. Brands with the high impact index were 'A', 'T', 'I', 'C' and 'B'. These brands were recognized as the core brands by consumers.

• Korean Journal of Agricultural Science
• /
• v.50 no.3
• /
• pp.527-538
• /
• 2023

In this study, we aimed to apply multispectral imaging (713 - 920 nm, 10 bands) for maturity classification and recognition of oriental melons grown in hydroponic greenhouses. A total of 20 oriental melons were selected, and time series multispectral imaging of oriental melons was 7 - 9 times for each sample from April 21, 2023, to May 12, 2023. We used several approaches, such as Savitzky-Golay (SG), standard normal variate (SNV), and Combination of SG and SNV (SG + SNV), for pre-processing the multispectral data. As a result, 713 - 759 nm bands were preprocessed with SG for the maturity classification of oriental melons. Additionally, a Light Gradient Boosting Machine (LightGBM) was used to train the recognition model for oriental melon. R² of recognition model were 0.92, 0.91 for the training and validation sets, respectively, and the F-scores were 96.6 and 79.4% for the training and testing sets, respectively. Therefore, multispectral imaging in the range of 713 - 920 nm can be used to classify oriental melons maturity and recognize their fruits.

• Journal of Advanced Marine Engineering and Technology
• /
• v.27 no.5
• /
• pp.641-647
• /
• 2003

The use of infrared range-finder sensor as the environment recognition system for mobile robot have the advantage of low sensing cost compared with the use of other vision sensor such as laser finder CCD camera. However, it is not easy to find the previous works on the use of infrared range-finder sensor for a mobile robot because of the non-linear characteristic of that. This paper describes the error due to non-linearity of a sensor and the correction of it using neural network. The neural network consists of multi-layer perception and Levenberg-Marquardt algorithm is applied to learning it. The effectiveness of the proposed algorithm is verified from experiment.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1992.10a
• /
• pp.266-270
• /
• 1992

In this study an active vision system using a laser range finder is proposed for the navigation of a mobile robot in unknown environment. The laser range finder consists of a slitted laser beam generator, a scanning mechanism, CCD camera, and a signal processing unit. A laser beam from laser source is slitted by a set of cylindrical lenses and the slitted laser beam is emitted up and down and rotates around the robot by the scanning mechanism. The image of laser beam reflected on the surface of an object is engraved on the CCD array. A high speed image processing algorithm is proposed for the real-time navigation of the mobile robot. Through experiments it is proved that the accurate and real-time recognition of environment is able to be realized using the proposed laser range finder.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 1999.10a
• /
• pp.99-104
• /
• 1999

This paper proposes an efficient method constructing a local map using the data of a scanning laser range finder. A laser range finder yields distance data of polar form, that is, distance data corresponding to every scanning directions. So, the data consists of directional angle and distance. We propose a new method to find a line fitting with a set of such data. The method uses Log-Hough Transformation. Usually, map building from these data requires some transformations between different coordinate systems. The new method alleviates such complication. Also, the method simplifies computation for line recognition and eliminates the slope quantization problems inherent in the classical Cartesian Hough transform method. To show the efficiency of the proposed method, it is applied to find a local map using the data from a laser range finder PLS(Proximity Laser Scanner, made by SICK).

• Journal of Sensor Science and Technology
• /
• v.33 no.4
• /
• pp.187-195
• /
• 2024

Light detection and ranging (LiDAR), a widely used sensor in mobile robots and autonomous vehicles, has its most important function as measuring the range of objects in three-dimensional space and generating point clouds. These point clouds consist of the coordinates of each reflection point and can be used for various tasks, such as obstacle detection and environment recognition. However, several processing steps are required, such as three-dimensional modeling, mesh generation, and rendering. Efficient data processing is crucial because LiDAR provides a large number of real-time measurements with high sampling frequencies. Despite the rapid development of controller computational power, simplifying the computational algorithm is still necessary. This paper presents a method for estimating the presence of curbs, humps, and ground tilt using range measurements from a single horizontal or vertical scan instead of point clouds. These features can be obtained by data segmentation based on linearization. The effectiveness of the proposed algorithm was verified by experiments in various environments.

• Culinary science and hospitality research
• /
• v.16 no.4
• /
• pp.28-42
• /
• 2010

The purpose of this study is to examine consumers' recognition, purchase intention, price acceptability of carving decoration, which can be said to be one part of food-space presentation, food styling, and table decoration. For this, a survey was carried out to target adults in over 20 years old who use a bus and a subway during morning and evening time in Daegu area from May 18, 2009 to May 22, 2009, and 296 copies were used for the final analysis. As a result of the research, over 50% of the consumers know about carving, saying they have come to mow it mostly through TV. Carving was mentioned to be probably used the most in buffet restaurants and other types of restaurants, and to be likely to be used the most in buffet restaurants and Japanese-style food Also, they responded that flower-butterfly carving & Japanese-style food, animal-form carving & Chinese-style food, and watermelon carving & buffet are harmonized the most. In addition, consumers with high recognition of carving decoration were indicated to be high in purchase intention and price acceptability. Also, Consumers with low recognition of carving decoration perceive very low price acceptability even if being high in purchase intention. However, when purchase intention of consumers with high recognition of carving decoration was high, price acceptability was indicted very highly.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.46 no.2
• /
• pp.92-99
• /
• 2009

This paper established the range of the wavelength of traffic lights to detection the color of traffic lights and the color component segmentation with the range of the wavelength. Development of traffic light automatic discrimination system is consists of the color detection and the traffic lights recognition. In this thesis, it established the range of the wavelength of traffic lights to detection the color of traffic lights and the color segmentation with the range of the wavelength. By the segmentation, the traffic light colors(red, orange and green) can be detected and the background is changed into gray image. Next, we proposed the algorithm which can detect the area of traffic lights in the various surroundings with the wavelet transformation algorithm. Also, we proposed traffic lights recognition algorithm using between the edge operator and the Hausdorff distance algorithm based on CBIR(Content-based Image retrieval). Therefore, the proposed algorithm is more superior to the conventional algorithm by experimenting with the illumination including the traffic lights and the backgrounds with various images.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.10 no.6
• /
• pp.609-616
• /
• 2017

In this paper, we propose an algorithm to obtain more stable and high recognition rate by using left and right rotation information of input image in order to obtain a stable recognition rate in face recognition. The proposed algorithm uses the facial image as the input information in the web camera environment to reduce the size of the image and normalize the information about the brightness and color to obtain the improved recognition rate. We apply Principal Component Analysis (PCA) to the detected candidate regions to obtain feature vectors and classify faces. Also, In order to reduce the error rate range of the recognition rate, a set of data with the left and right $45^{\circ}$ rotation information is constructed considering the directionality of the input face image, and each feature vector is obtained with PCA. In order to obtain a stable recognition rate with the obtained feature vector, it is after scattered in the eigenspace and the final face is recognized by comparing euclidean distant distances to each feature. The PCA-based feature vector is low-dimensional data, but there is no problem in expressing the face, and the recognition speed can be fast because of the small amount of calculation. The method proposed in this paper can improve the safety and accuracy of recognition and recognition rate faster than other algorithms, and can be used for real-time recognition system.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.49 no.9
• /
• pp.307-313
• /
• 2012

This paper proposes a hand-eye laser range finder (LRF) based welding plane recognition method for autonomous robotic welding. The robot welding is the process of joining a metal piece and the welding plane along the welding path predefined by the shape of the metal piece. Thus, for successful robotic welding, the position and direction of the welding plane should be exactly detected. If the detected position and direction of the plane is not accurate, the autonomous robotic welding should fail. For precise recognition of the welding plane, a line on the plane is detected by the LRF. For obtaining the line on the plane, the Hough transform is applied to the obtained data from the LRF. Since the Hough transform is based on the voting method, the sensor noise can be reduced. Two lines on the plane are obtained before and after rotation of the robot joint, and then the direction of the plane is calculated by the cross product of two direction vectors of two lines. For verifying the feasibility of the proposed method, the simulation with the robot simulator, RoboticsLab developed by Simlab Co. Ltd., is carried out.