• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.9 no.7
• /
• pp.1513-1517
• /
• 2005

In this paper, I make use of a Multi-Channel skin color model with Hue, Cb, Cg using Red, Blue, Green channel altogether which remove bight component as being consider the characteristics of skin color to do modeling more effective to a facial skin color for extracting a facial area. 1 used efficient HOLA(Higher order local autocorrelation function) using 26 feature vectors to obtain both feature vectors of a facial area and the edge image extraction using Harr wavelet in image which split a facial area. Calculated feature vectors are used of date for the facial recognition through learning of neural network It demonstrate improvement in both the recognition rate and speed by proposed algorithm through simulation.

• The Journal of the Korea Contents Association
• /
• v.7 no.12
• /
• pp.311-321
• /
• 2007

For fast and robust face detection, this paper proposes an approach for face detection using fusion of heterogeneous template matching. First, we detect skin regions using a model of skin color which covers various illumination and races. After reducing a search space by region labelling and filtering, we apply template matching with skin color and edge to the detected regions. Finally, we detect a face by finding the best choice of template fusion. Experimental results show the proposed approach is more robust in skin color-like environments than with a single template matching and is fast by reducing a search space to face candidate regions. Also, using a global accumulator can reduce excessive space requirements of template matching.

• The Journal of the Korea Contents Association
• /
• v.5 no.2
• /
• pp.267-274
• /
• 2005

In this paper, we proposed an algorithm which cognize hand pose in real time using only image. Hand recognizes using edge orientation histogram which comes under a constant quantity of 2D appearance because hand pose is intricate. This method suit hand pose recognition in real time because it extracts hand space accurately, has little computation quantify, and is less sensitive to lighting change using color information in complicated background. Method which reduces recognition error using principal component analysis method to can recognize through hand shape presentation direction change is explained. A case that hand shape changes by turning 3D also by using this method is possible to recognize. Besides, principal component space creation time is reduced remarkably because edge directional data is used.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2002.05a
• /
• pp.585-589
• /
• 2002

In this paper, hierarchical retrieval system based on efficient feature extraction is proposed. In order to retrieval the image with robustness for geometrical transformation such as translation, scaling, and rotation. After performing the 2-level wavelet transform on image, We extract moment in low-level subband which was subdivided into subimages and texture feature, contrast of GLCM(Gray Level Co-occurrence Matrix). At first we retrieve the candidate images in database by the ones of image. To perform a more accurate image retrieval, the edge information on the high-level subband was subdivided horizontally, vertically and diagonally. And then, the energy rate of edge per direction was determined and used to compare the energy rate of edge between images for higher accuracy.

• Journal of Korean Port Research
• /
• v.13 no.2
• /
• pp.303-312
• /
• 1999

The automated gate operating system is developed in this paper that controls the information of container at gate in the ACT. This system can be divided into three parts and consists of container identifier recognition car plate recognition container deformation perception. We linked each system and organized efficient gate operating system. To recognize container identifier the preprocess using LSPRD(Line Scan Proper Region Detection)is performed and the identifier is recognized by using neural network MBP When car plate is recognized only car image is extracted by using color information of car and hough transform. In the port of container deformation perception firstly background is removed by using moving window. Secondly edge is detected from the image removed characters on the surface of container deformation perception firstly background is removed by using moving window. Secondly edge is detected from the image removed characters on the surface of container. Thirdly edge is fitted into line segment so that container deformation is perceived. As a results of the experiment with this algorithm superior rate of identifier recognition is shown and the car plate recognition system and container deformation perception that are applied in real-time are developed.

• Journal of Digital Contents Society
• /
• v.10 no.2
• /
• pp.319-326
• /
• 2009

In this paper, we present an algorithm which recognize hand shape in real time using only image without adhering separate sensor. Hand recognizes using edge orientation histogram, which comes under a constant quantity of 2D appearances because hand shape is intricate. This method suit hand pose recognition in real time because it extracts hand space accurately, has little computation quantity, and is less sensitive to lighting change using color information in complicated background. Method which reduces recognition error using principal component analysis(PCA) method to can recognize through hand shape presentation direction change is explained. A case that hand shape changes by turning 3D also by using this method is possible to recognize. Human interface system manufacture technique, which controls a home electric appliance or game using, suggested method at experience could be applied.

• Journal of Fashion Business
• /
• v.27 no.6
• /
• pp.66-84
• /
• 2023

Handbags are a part of fashion and while their significance and value are increasing, research on this topic is lacking. This study defines handbags and categorizes the materials used for making handbags, sewing methods, expression techniques, and terminologies related to accessories. A total of 1,743 handbags that were released from the Spring 2020 to Fall 2023, Ready-to-Wear collections by 8 selected brands (Hermes, Dior, Fendi, Chanel, Louis Vuitton, Prada, Gucci, and Alexander McQueen), were analyzed. Out of these, 732 unique designs, excluding those with only color variations, were studied. The most common sewing methods were 'Cut, sewing, and edge painting', 'Cylinder arm sewing', 'Cut, edge painting, and sewing', and 'Inverted seam', in that order. Slim strap designs primarily used the 'Cut, sewing, and edge painting' method, whereas the body, especially with narrow and hard leather, was best suited for the 'Cylinder arm sewing machine'. For expression techniques, the most frequently used methods were 'Quilting', 'Metal Eyelet', 'Embossing', 'Printing', 'Punching', and 'Weaving', respectively. The characteristics of each brand's production methods, expression techniques, and accessories were as follows: First, the exposure of logos and monograms is prominent. Unlike clothing, handbags often prominently feature the brand's logo or monogram. Second, signature quilting is a prominent feature. Quilting effectively conveys the brand's signature style, providing cushioning, volume, and pattern effects. Third, sustainable development is a growing trend. Brands are increasingly applying eco-friendly and socially responsible designs.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2008.05a
• /
• pp.801-804
• /
• 2008

During face recognition process, face detection process is most preceding process. However, face has very high floating property, so the result could be very different according to which method we used. This paper studies about eye detection and eye blinking verification using edge and color information from YCbCr distribution map, segmentation, and labeling methods.

• International Journal of Contents
• /
• v.12 no.1
• /
• pp.1-5
• /
• 2016

To manipulate large video contents, effective video indexing and retrieval are required. A large number of video indexing and retrieval algorithms have been presented for frame-wise user query or video content query whereas a relatively few video sequence matching algorithms have been proposed for video sequence query. In this paper, we propose an efficient algorithm that extracts key frames using color histograms and matches the video sequences using edge features. To effectively match video sequences with a low computational load, we make use of the key frames extracted by the cumulative measure and the distance between key frames, and compare two sets of key frames using the modified Hausdorff distance. Experimental results with real sequence show that the proposed video sequence matching algorithm using edge features yields the higher accuracy and performance than conventional methods such as histogram difference, Euclidean metric, Battachaya distance, and directed divergence methods.

• 한국정보디스플레이학회:학술대회논문집
• /
• 2008.10a
• /
• pp.1573-1576
• /
• 2008

A simulation system is developed to calculate the apparent motion-induced image from a sequence of temporal luminance transitions, while using the properties of the human visual system. Based on the simulation method, both edge (moving block) and detail degradation (line spreading, grating, sinusoidal pattern), and also color aberration are discussed.