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Subject: search.filters.subject.Image retrieval

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    Using image features and eye tracking device to predict human emotions towards abstract images
    (2016-01-01)
    Pasupa, Kitsuchart
    ;
    Chatkamjuncharoen, Panawee
    ;
    Wuttilertdeshar, Chotiros
    ;
    Sugimoto, Masanori
    Nowadays, emotional semantic image retrieval system enables users to access images that they want in a database according to emotional concept. This leads to affective image classification task which recently attracts researchers’ attention. However, different users may experience different emotions depending on where, in the image, they are gazing on. This paper presents an improved prediction method by taking into account the users eye movement as implicit feedback while they are looking at the image. Our experimental results show that using both eye movement information and image feature together to determine users emotion gave more accurate predictions than using image feature alone.
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    Remote sensing image retrieval using DCT-based texture descriptor
    (2016-01-01)
    Nuangnit, Atcharawan
    ;
    Rangsanseri, Yuttapong
    In this paper, we propose an image retrieval technique using texture descriptor extracted from a block-based Discrete Cosine Transform (DCT) of the image. To construct the texture descriptor, the absolute DCT coefficients are averaged over the entire image, and the feature vector is formed up by choosing middle-frequency elements of the zigzag-scanned DCT coefficients. This extraction is applied to both query image and all images in the archive. A distance function is used to measure the similarity between two images. This technique is successfully applied to remote sensing images downloaded from www.earthexpolrer.usgs.gov of Thailand regions.
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    Image retrieval using connected color region and moment invariants
    (2007-12-01)
    Dongphontong, Daungkamol
    ;
    Chitsobhuk, Orachat
    In this paper, combined descriptors of Connected Color Region (CCR) and moment invariants are proposed as color features for a Content-Based Image Retrieval system. CCR provides the spatial information and maximum co-occurrence color while moment invariants help to better distinguish different distribution of colors in the image. From the experiments, the retrieval results using only CCR descriptors depend on CCR block size. The smaller the size of the block, the higher the retrieval performance. However, if the block size is small, it requires longer retrieval time. Therefore, in this paper, color moment is introduced as additional feature to CCR descriptors to help compromising between retrieval performance and time. The retrieval results using both CCR with large block size and moment descriptors are comparable to those of using only CCR with small block size while require less amount of retrieval time.
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    Image retrieval using haar color descriptor incorporating with pruning techniques
    (2007-07-03)
    Utenpattanant, Ariya
    ;
    Chitsobhuk, Orachat
    This paper presents a content-based image retrieval system using a compact color descriptor (63-bit binary Haar color descriptor) incorporating with pruning techniques. The objective of pruning is to look for the candidate images similar to the query image from the database and ignore the rest that are not likely to the query image. Several statistical pruning criteria are experimented in order to achieve faster retrieval time while preserve good retrieval performance. After the pruning process, the descriptors of the candidate images are then matched with that of the query. The most similar images will be retrieved and ordered according to their distance to the query. The proposed technique is evaluated based on different sizes of the database. The experimental results show good retrieval performance over a variety of image collections.
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    Color descriptor for image retrieval in wavelet domain
    (2006-01-01)
    Utenpattanant, Ariya
    ;
    Chitsobhuk, Orachat
    ;
    Khawne, Amnach
    This paper presents an approach to manage a large database using a compact color descriptor and a statistical method for accurately pruning the database. A compact color descriptor adopted in the proposed content-based image retrieval system is 63-bit binary Haar color histogram, which is very compact and can be effectively used for fast image search. In addition to fast searching using this compact descriptor, we further improve retrieval time by applying pruning technique, which looks for the candidate images similar to the query image from the database and ignore the rest that are not likely to the query image. The descriptors of the candidate images are then matched with that of the query. The most similar images will be retrieved and ordered according to their distance to the query. The proposed retrieval system can efficiently retrieve the most similar images from the database while can help reducing the retrieval time and the storage space.