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Information retrieval in document image databases 总被引:2,自引:0,他引:2
Yje Lu Chew Lim Tan 《Knowledge and Data Engineering, IEEE Transactions on》2004,16(11):1398-1410
With the rising popularity and importance of document images as an information source, information retrieval in document image databases has become a growing and challenging problem. In this paper, we propose an approach with the capability of matching partial word images to address two issues in document image retrieval: word spotting and similarity measurement between documents. First, each word image is represented by a primitive string. Then, an inexact string matching technique is utilized to measure the similarity between the two primitive strings generated from two word images. Based on the similarity, we can estimate how a word image is relevant to the other and, thereby, decide whether one is a portion of the other. To deal with various character fonts, we use a primitive string which is tolerant to serif and font differences to represent a word image. Using this technique of inexact string matching, our method is able to successfully handle the problem of heavily touching characters. Experimental results on a variety of document image databases confirm the feasibility, validity, and efficiency of our proposed approach in document image retrieval. 相似文献
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Recent technological advances have made it possible to process and store large amounts of image data. Perhaps the most impressive example is the accumulation of image data in scientific applications such as medical or satellite imagery. However, in order to realize their full potential, tools for efficient extraction of information and for intelligent searches in image databases need to be developed. This paper describes a new approach to image data retrieval which allows queries to be composed of local intensity patterns. The intensity pattern is converted into a feature representation of reduced dimensionality which can be used for searching similar-looking patterns in the database. This representation is obtained by filtering the pattern with a bank of scale and orientation selective filters modeled using Gabor functions. Experimental results are presented which illustrate that the proposed representation preserves the perceptual similarities, and provides a powerful tool for content-based image retrieval. 相似文献
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Michael Edberg Hansen Author Vitae Jens Michael Carstensen Author Vitae 《Pattern recognition》2004,37(11):2155-2164
Many image classification problems can fruitfully be thought of as image retrieval in a “high similarity image database” (HSID) characterized by being tuned towards a specific application and having a high degree of visual similarity between entries that should be distinguished. We introduce a method for HSID retrieval using a similarity measure based on a linear combination of Jeffreys-Matusita distances between distributions of local (pixelwise) features estimated from a set of automatically and consistently defined image regions. The weight coefficients are estimated based on optimal retrieval performance. Experimental results on the difficult task of visually identifying clones of fungal colonies grown in a petri dish and categorization of pelts show a high retrieval accuracy of the method when combined with standardized sample preparation and image acquisition. 相似文献
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Virtual images for similarity retrieval in image databases 总被引:1,自引:0,他引:1
Petraglia G. Sebillo M. Tucci M. Tortora G. 《Knowledge and Data Engineering, IEEE Transactions on》2001,13(6):951-967
We introduce the virtual image, an iconic index suited for pictorial information access in a pictorial database, and a similarity retrieval approach based on virtual images to perform content-based retrieval. A virtual image represents the spatial information contained in a real image in explicit form by means of a set of spatial relations. This is useful to efficiently compute the similarity between a query and an image in the database. We also show that virtual images support real-world applications that require translation, reflection, and/or rotation invariance of image representation 相似文献
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《Pattern recognition letters》2001,22(3-4):323-337
This paper presents a scheme of image retrieval from a database using queries prompted by the colour and the shape of the objects present in different scenes. Of the whole scheme of image retrieval, we will focus attention on the modules that allow feature extraction of the component objects from the scenes and the matching of the objects among the different images. The defined scheme enables the indexing of images by measuring the similarity between the integral objects. 相似文献
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WALRUS: a similarity retrieval algorithm for image databases 总被引:2,自引:0,他引:2
Natsev A. Rajeev Rastogi Shim K. 《Knowledge and Data Engineering, IEEE Transactions on》2004,16(3):301-316
Approaches for content-based image querying typically extract a single signature from each image based on color, texture, or shape features. The images returned as the query result are then the ones whose signatures are closest to the signature of the query image. While efficient for simple images, such methods do not work well for complex scenes since they fail to retrieve images that match the query only partially, that is, only certain regions of the image match. This inefficiency leads to the discarding of images that may be semantically very similar to the query image since they may contain the same objects. The problem becomes even more apparent when we consider scaled or translated versions of the similar objects. We propose WALRUS (wavelet-based retrieval of user-specified scenes), a novel similarity retrieval algorithm that is robust to scaling and translation of objects within an image. WALRUS employs a novel similarity model in which each image is first decomposed into its regions and the similarity measure between a pair of images is then defined to be the fraction of the area of the two images covered by matching regions from the images. In order to extract regions for an image, WALRUS considers sliding windows of varying sizes and then clusters them based on the proximity of their signatures. An efficient dynamic programming algorithm is used to compute wavelet-based signatures for the sliding windows. Experimental results on real-life data sets corroborate the effectiveness of WALRUS'S similarity model. 相似文献
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A similarity measure for silhouettes of 2D objects is presented, and its properties are analyzed with respect to retrieval of similar objects in image databases. To reduce influence of digitization noise as well as segmentation errors the shapes are simplified by a new process of digital curve evolution. To compute our similarity measure, we first establish the best possible correspondence of visual parts (without explicitly computing the visual parts). Then the similarity between corresponding parts is computed and summed. Experimental results show that our shape matching procedure gives an intuitive shape correspondence and is stable with respect to noise distortions. 相似文献
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Justine LebrunPhilippe-Henri Gosselin Sylvie Philipp-Foliguet 《Image and vision computing》2011,29(11):716-729
In the framework of online object retrieval with learning, we address the problem of graph matching using kernel functions. An image is represented by a graph of regions where the edges represent the spatial relationships. Kernels on graphs are built from kernel on walks in the graph. This paper firstly proposes new kernels on graphs and on walks, which are very efficient for graphs of regions. Secondly we propose fast solutions for exact or approximate computation of these kernels. Thirdly we show results for the retrieval of images containing a specific object with the help of very few examples and counter-examples in the framework of an active retrieval scheme. 相似文献
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Multimedia Tools and Applications - With the development of different image capturing devices, huge amount of complex images are being produced everyday. Easy access to such images requires proper... 相似文献
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《Pattern recognition letters》2002,23(1-3):113-126
Since the number of registered trademarks is increasing rapidly, the job of identifying infringement of similar trademarks by human inspection becomes laborious and time-consuming. To deal with the problem, we propose an automatic content-based trademark retrieval method. The proposed method automatically selects appropriate features based on feature selection principles to discriminate trademarks. The database trademarks are softly clustered into classes using a fuzzy approach to increase the retrieval speed. The user can submit a query through trademark examples to get a list of database trademarks ordered by similarity ranks. The query results can be iteratively refined by the feedback presented by the user until the trademarks of interest are retrieved. Experiments are conducted on a trademark database containing 1000 images and the retrieval results are very encouraging. 相似文献
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提出了一种隐私语义保持的图像内容检索方法,将加密图像中隐私保持尺度不变特征变换(SIFT)的提取方法和二进制SIFT算法融合在一起,不仅保证了上传到服务器端的图像是加密的,同时又能在加密空间保持其隐私语义.对图像进行Paillier同态加密,保证了图像在服务器端和传输过程中的安全性,在加密域提取SIFT特征,并将其用二进制表示,减少存储空间和计算复杂度.实验证明:经原始图像特征提取后生成的二进制SIFT在稳健性测试中获得良好的效果,并且与加密图像特征提取后生成的二进制SIFT保持等距,在明文域和密文域中保持了图像搜索匹配的准确性,在匹配效率上得到提高. 相似文献
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基于内容的图像检索技术与医学图像检索 总被引:5,自引:1,他引:4
姜洪溪 《计算机工程与设计》2004,25(6):899-900,928
在分析基于内容的图像检索技术特点的基础上,提出了4种基于内容的图像检索方法,并对每种方法的实现特别是特征抽取进行了一定的研究。根据医学图像的使用特点,对基于内容的医学图像检索技术进行了初步的研究;对医学图像特征的抽取,应将重点放在形状特征和纹理特征的抽取上;同时,对医学图像进行检索,还可以使用颜色空间分布特征,来进一步进行相似匹配。 相似文献