• Journal of the Semiconductor & Display Technology
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• v.13 no.2
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• pp.45-52
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• 2014

This paper proposes an efficient photo retrieval system that automatically indexes for searching of relevant images, using a combination of geo-coded information, direction/location of image capture device and content-based visual features. A photo image is labeled with its GPS (Global Positioning System) coordinates and direction of the camera view at the moment of capture, and the label leads to generate a geo-spatial index with three core elements of latitude, longitude and viewing direction. Then, content-based visual features are extracted and combined with the geo-spatial information, for indexing and retrieving the photo images. For user's querying process, the proposed method adopts two steps as a progressive approach, filtering the relevant subset prior to use a content-based ranking function. To evaluate the performance of the proposed scheme, we assess the simulation performance in terms of average precision and F-score, using a natural photo collection. Comparing the proposed approach to retrieve using only visual features, an improvement of 20.8% was observed. The experimental results show that the proposed method exhibited a significant enhancement of around 7.2% in retrieval effectiveness, compared to previous work. These results reveal that a combination of context and content analysis is markedly more efficient and meaningful that using only visual feature for image search.

• Journal of the Semiconductor & Display Technology
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• v.7 no.4
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• pp.57-62
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• 2008

Image retrieval is one of the most exciting and rapidly growing research issues in the field of multimedia technology. This paper proposes a new method that performs search the relevant images by using query-by-example. The proposed method for search and retrieval of images utilizes the location information where the image had been taken. The system associates the photo images with their corresponding GPS coordinates that are used as metadata for searching. Experimental results show that the proposed method demonstrates better performance improving up to 59% of average recall and 49% of average precision. Moreover, we learned from the experimental results geo-location information embedded within the image header is more effective and positive on the search and storage.

• Journal of the Semiconductor & Display Technology
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• v.19 no.4
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• pp.135-138
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• 2020

This paper suggests a method of automatic clustering to search of relevant digital photos using geo-coded information. The provided scheme labels photo images with their corresponding global positioning system coordinates and date/time at the moment of capture, and the labels are used as clustering metadata of the images when they are in the use of retrieval. Experimental results show that geo-location information can improve the accuracy of image retrieval, and the information embedded within the images are effective and precise on the image clustering.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.3A
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• pp.258-267
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• 2002

We present an image retrieval method for improving retrieval performance by effective fusion of entropy features in wavelet region and wavelet moments. In this method, entropy features are sensitive to the local variation of gray level and well extract valley and edges. These features are effectively applied to contend-based image retrieval by well fusing to wavelet moments that represent texture property in multi-resolution. In order to evaluate the performance of the proposed method. We use Corel Draw Photo DB. Experiment results show that the proposed yields 11% better performance for Corel Draw Photo DB over wavelet moments method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.4
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• pp.434-441
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• 2001

We present an image retrieval method for improving retrieval performance by the effective fusion of spatial histogram and wavelet moments. In this method, the similarity for spatial histograms and the similarity for wavelet moment are effectively fused in the computation of the similarity between a query image and DB image. That is, the wavelet moments feature represented in multi-resolution and the spatial histogram feature robust to translation and rotation are used to improve retrieval performance. In order to evaluate the performance of the proposed method, we use Brodatz texture DB, MPEG-7 T1 DB, and Corel Draw Photo DB. Experimental results show that the proposed method yields 5.3% and 13.8% better Performances for Brodatz DB, and 15.5% and 3.2% better Performances for Corel Draw Photo DB over the histogram method and the wavelet moment method, respectively.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.11-14
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• 2000

We present an image retrieval method that improves retrieval rate by using the fusion of histogram and wavelet moment features. The key idea is that images similar to a query image are selected in DB by using the wavelet moment features. Then the result images are retrieved from the selected images by using histogram method. In order to evaluate the performance of the proposed method, we use Brodatz texture database, MPEG-7 T1 database and Corel Draw photo. Experimental result shows that the proposed method is better than each of histogram method and wavelet moment method.

• Journal of the Semiconductor & Display Technology
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• v.18 no.4
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• pp.57-61
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• 2019

Nowadays, portable digital cameras such as smart phone cameras are being popularly used for entertainment and visual information recording. Given a database of geo-tagged images, a visual location recognition system can determine the place depicted in a query photo. One of the most common visual location recognition approaches is the bag-of-words method where local image features are clustered into visual words. In this paper, we propose a new bag-of-words-based visual location recognition algorithm using time-series streetview database. The proposed algorithm selects only a small subset of image features which will be used in image retrieval process. By reducing the number of features to be used, the proposed algorithm can reduce the memory requirement of the image database and accelerate the retrieval process.

• Journal of the Semiconductor & Display Technology
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• v.7 no.3
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• pp.59-63
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• 2008

Geo-coding refers to the process of associating data with location information, and the system deals with geographic identifiers expressed as latitude and longitude or street addresses. Although many services have been launched, there still remains a problem for users to create geo-coded photo with manually labeling GPS(Global Positioning System) coordinate or synchronizing with separate devices. In this paper, we design and implement a geo-coding system which utilizes the time and location information embedded in digital photographs in order to automatically categorize a personal photo collection. An included GPS receiver labels a photograph with its corresponding GPS coordinates, and the position of the camera is automatically recorded into the photo image header at the moment of capture. The place and time where the photo was taken allows us to provide context metadata on the management and retrieval of information.

• Journal of Information Management
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• v.31 no.4
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• pp.50-70
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• 2000

Since the contents of internet resources are beginning to include texts, images and sounds, different Web-based image search engines have been developed accordingly. It is a fact that these diversities of multimedia contents have made search process and retrieval of relevant information very difficult. The purpose of the study is to compare and evaluate its special features and performance of the existing image search engines in order to provide user help to select appropriate search engines. The study selected AV Photo Finder, Lycos MultiMedia, Amazing Picture Machine, Image Surfer, WebSeek, Ditto for comparison and evaluation because of their reputations of popularity among users of image search engines. The methodology of the study was to analyze previous related literature and establish criteria for the evaluation of image search engines. The study investigated characteristics, indexing methods, search capabilities, screen display and user interfaces of different search engines for the purpose of comparison of its performance. Finally, the study measured relative recall and precision ratios to evaluate their electiveness of retrieval under the experimental set up. Results of the comparative analysis in regard to its search performance are as follows. AV Photo Finder marked the highest rank among other image search engines. Ditto and WebSeek also showed comparatively high precision ratio. Lycos MultiMedia and Image Surfer follows after them. Amazing Picture Machine stowed the lowest in ranking.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.703-712
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• 2003

With the explosive growth n the numbers and sizes of imaging technologies, Content-Based Image Retrieval (CBIR) has been attacked the interests of researchers in the fields of digital libraries, image processing, and database systems. In general, in the case of query-by-image, in user has to select an image from database to query, even though it is not his completely desired one. However, since query-by-sketch approach draws a query shape according to the user´s desire it can provide more high-level searching interface to the user compared to the query-b-image. As a result, query-by-sketch has been widely used. In this paper, we propose a Java-based image retrieval system that consists of sketch query and image classification. We use two features such as color histogram and Haar wavelets coefficients to search similar images. Then the Leave-One-Out method is used to classify database images. The categories of classification are photo & painting, city & nature, and sub-classification of nature image. By using the sketch query and image classification, w can offer convenient image retrieval interface to user and we can also reduce the searching time.