• Journal of the Korea Society of Computer and Information
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• v.14 no.8
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• pp.51-58
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• 2009

In this paper. we propose search algorithm using Low Peak Feature of audio and image color value by which similar movies can be identified. Combing through entire video files for the purpose of recognizing and retrieving matching movies requires much time and memory space. Moreover, these methods still share a critical problem of erroneously recognizing as being different matching videos that have been altered only in resolution or converted merely with a different codec. Thus we present here a similar-video-retrieval method that relies on analysis of audio patterns, whose peak features are not greatly affected by changes in the resolution or codec used and image color values. which are used for similarity comparison. The method showed a 97.7% search success rate, given a set of 2,000 video files whose audio-bit-rate had been altered or were purposefully written in a different codec.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.33-40
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• 2023

The mainstay of current image recovery frameworks is Content-Based Image Retrieval (CBIR). The most distinctive retrieval method involves the submission of an image query, after which the system extracts visual characteristics such as shape, color, and texture from the images. Most of the techniques use RGB color space to extract and classify images as it is the default color space of the images when those techniques fail to change the color space of the images. To determine the most effective color space for retrieving images, this research discusses the transformation of RGB to different color spaces, feature extraction, and usage of Convolutional Neural Networks for retrieval.

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.91-97
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• 2009

This paper proposes novel FE-CBIRS that finds best position of a cut to be retrieved based on color feature distribution in digital contents of IPTV. Conventional CBIRS have used a method that utilizes both color and shape information together to classify images, as well as a method that utilizes both feature information of the entire region and feature information of a partial region that is extracted by segmentation for searching. Also, in the algorithm, average, standard deviation and skewness values are used in case of color features for each hue, saturation and intensity values respectively. Furthermore, in case of using partial regions, only a few major colors are used and in case of shape features, the invariant moment is mainly used on the extracted partial regions. Due to these reasons, some problems have been issued in CBIRS in processing time and accuracy so far. Therefore, in order to tackle these problems, this paper proposes the FE-CBIRS that makes searching speed faster by classifying and indexing the extracted color information by each class and by using several cuts that are restricted in range as comparative images.

• Journal of the Korea Furniture Society
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• v.24 no.4
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• pp.416-425
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• 2013

Luis Barragan's Architecture has creative feature that Mexican environment and traditional culture were complete by color. Thus the color of his work makes our emotions rich and colorful. He said "My architecture is autobiographical..." at speech in Pritz price. As we can see in his architectural philosophy that sentimental architecture is important than theorical system, his works are impression of empirical factor with intuition. "Color is a complement to the architecture. It serve to enlarge or reduce a space. It's also useful for adding that touch of magic a place needs", stated Barragan. During his process of shaping space, Barragan drew on color in the same way as an architectural component, according it a spatial funtion and expressive vale. he allied it with light, deeming it a crucial vehical for conveying the emotive attributes a site. The capacity of color to express sensitivity and sensuality within an architecture space is liked to its psycho-physiological qualities. In this kind of view, color featyre in Barragan's work is one of the most important tools to realize sentimental architecture, not only is result of the Mexican regional color. As a result, make focus on analyzing various meaning of the color in Barragan's architecture like poetic and habitable structure.

• The KIPS Transactions:PartB
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• v.13B no.3 s.106
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• pp.205-214
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• 2006

Texts in images have significant and detailed information about the scenes, and if we can automatically detect and recognize those texts in real-time, it can be used in various applications. In this paper, we propose a new text detection method that can find texts from the various camera-captured images and propose a text segmentation method from the detected text regions. The detection method proposes color variance as a detection feature in RGB color space, and the segmentation method suggests an improved K-means color clustering in RGB color space. We have tested the proposed methods using various kinds of document style and natural scene images captured by digital cameras and mobile-phone camera, and we also tested the method with a portion of ICDAR[1] contest images.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6C
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• pp.610-618
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• 2002

This paper presents a new image retrieval method that is based on color space and block region information. The color space information of images can be obtained by color binary set, and the block region information can be obtained by regional segmentation and feature. The candidate images are decided by comparing with color features and its binary set of query image and image feature database for retrieval. Particularly, it is possible that the retrieval using similarity-measurements has the weights of color spatial distribution arid its objective block region features. This retrieval method using color spatial and block region features is shown with the effectiveness on the result of implementation on image database with 6,000 images.

• Korean Institute of Interior Design Journal
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• no.34
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• pp.114-123
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• 2002

Koreans have regarded the red as a major color from old times. The red is a traditional color to have symbols of high position, national foundation and especially royalty. So, we can see the reds in the palace for kings very much.The purpose of this study is to draw out the features of color red in the Kyungbok palace. The color was analyzed by two categories-architectural buildings${\cdot}$structures and ornamental painted patterns. The major findings from this research are summarized as follows:1. Seokganju(similar to terra rossa) and toyugsaek(light seokganju) are found main colors in architectural space, while seokganju has a linear effect and toyuk has a facial effect. 2. Yugsaek(similar to light vermillion) and Jangdan(similar to orange) are found main colors in ornamental painted patterns. These colors are more vivid and brighter than those for architectural space.3. As for two-color combination, reds and blues(including greens) are found major combination both of architectural space and ornamental patterns. And reds and white are the following combination, which gives an bright image by white. 4. As for three-color combination, red-white-black combination of pediment and red-blue-white combination of openings are found very popular in architectural space, while red-blue-yellow combination is most popular in ornamental patterns.The reds are found dominant color of both architectural space and ornamental patterns in the Kyungbok palace. The color design as shown in the Kyungbok palace can be considered as the feature of traditional color design.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.40-48
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• 2021

Content-Based Image Retrieval (CBIR) system plays a vital role to retrieve the relevant images as per the user perception from the huge database is a challenging task. Images are represented is to employ a combination of low-level features as per their visual content to form a feature vector. To reduce the search time of a large database while retrieving images, a novel image retrieval technique based on feature dimensionality reduction is being proposed with the exploit of metaheuristic optimization techniques based on Genetic Algorithm (GA), Extended Binary Cuckoo Search (EBCS) and Whale Optimization Algorithm (WOA). Each image in the database is indexed using a feature vector comprising of fuzzified based color histogram descriptor for color and Median binary pattern were derived in the color space from HSI for texture feature variants respectively. Finally, results are being compared in terms of Precision, Recall, F-measure, Accuracy, and error rate with benchmark classification algorithms (Linear discriminant analysis, CatBoost, Extra Trees, Random Forest, Naive Bayes, light gradient boosting, Extreme gradient boosting, k-NN, and Ridge) to validate the efficiency of the proposed approach. Finally, a ranking of the techniques using TOPSIS has been considered choosing the best feature selection technique based on different model parameters.

• The KIPS Transactions:PartB
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• v.11B no.5
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• pp.581-586
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• 2004

In this paper, we proposed a content-based image retrieval using a color feature for central region and its optimized comparing bin method. Human's visual characteristic is influenced by existent of central object. So we supposed that object is centrally located in image and then we extract color feature at central region. When the background of image is simple, the retrieval result can be bad affected by major color of background. Our method overcome this drawback as a result of the human visual characteristic. After we transform Image into HSV color space, we extract color feature from the quantized image with 16 level. The experimental results showed that the method using the eight high rank bin is better than using the 16 bin The case which extracts the feature with image's central region was superior compare with the case which extracts the feature with the whole image about 5%.

• Smart Media Journal
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• v.2 no.1
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• pp.31-36
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• 2013

A robust and efficient text extraction is very important for an accuracy of Optical Character Recognition (OCR) systems. Natural scene images with degradations such as uneven illumination, perspective distortion, complex background and multi color text give many challenges to computer vision task, especially in text extraction. In this paper, we propose a method for extraction of the text in signboard images based on a combination of mean shift algorithm and weighting scheme of hue and saturation in HSI color space for clustering algorithm. The number of clusters is determined automatically by mean shift-based density estimation, in which local clusters are estimated by repeatedly searching for higher density points in feature vector space. Weighting scheme of hue and saturation is used for formulation a new distance measure in cylindrical coordinate for text extraction. The obtained experimental results through various natural scene images are presented to demonstrate the effectiveness of our approach.