&lt;title&gt;Content-based indexing technique using relative geometry features&lt;/title&gt;

Hou, Tai-Yuan; Hsu, Arding; Liu, Peiya; Chiu, Ming-Yee

doi:10.1117/12.58493

Cited by 34 publications

(20 citation statements)

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“…The queries are specified explicitly by providing the desired feature values or implicitly by specifying an example image. Some system also uses the spatial organization of the image features, so that similarity is determined not only by the existence of certain features but also by their absolute or relative location in the image (Hou, et al, 1992;Bach, et al, 1996;Stricker and Dimai, 1996;Smith, 1997;Das, et al, 1997;Cohen, 1999). Early systems focused on the search engine (given a query, find the best matches) and did not use precious queries to understand better what the user was looking for.…”

Section: Related Workmentioning

confidence: 99%

Development of an Image Retrieval Model for Biomedical Image Databases

Philip¹,

Afolabi²,

Oluwaranti³

et al. 2011

Efficient Decision Support Systems - Practice and Challenges in Biomedical Related Domain

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Section: Related Workmentioning

confidence: 99%

Development of an Image Retrieval Model for Biomedical Image Databases

Philip¹,

Afolabi²,

Oluwaranti³

et al. 2011

Efficient Decision Support Systems - Practice and Challenges in Biomedical Related Domain

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“…Second, in order to satisfy the necessary condition (8), it suffices to verify the following equivalent condition…”

Section: Case Ii1bmentioning

confidence: 99%

“…It is obvious that the necessary condition (8) holds, but the size requirement of a possible exact picture-matching between Q 7 and f 3 is still not met (since there is no way for {x, y, z} in Q 7 matching {a, b} in f 7 ). Nevertheless, the necessary condition (8) is useful to exclude the database pictures, which fail the basic size requirement imposed by (8), from further picture-matching. Now the stepwise approximation algorithm needs to determine that, given 1 .…”

mentioning

confidence: 99%

A Stepwise Approximation of Intractable Spatial Constraints in Image Queries

Zhang¹,

Yau²

2003

Communications in Information and Systems

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Abstract. An image stored in image database systems is assumed to be associated with some content-based meta-data about that image, that is, information about objects in the image and absolute/relative spatial relationships among them. An image query for such an image database system can generally be handled in two ways: exact picture matching and approximate picture matching. We address the approximate picture matching problem of central interest in this paper, and present a stepwise approximation of intractable spatial constraints in an image query. Especially, this stepwise approximation may be pre-processed on an image query before an advanced picture matching algorithm is invoked. We then work out details of the stepwise approximation algorithm by analyzing, one by one, all possible 16 cases for results of the object matching step. Our analysis turns out that only 13 cases are valid, while the other 3 cases are identified impossible for finding an exact picture-matching between a query picture and a database picture. The worst-case running time complexity is given for each of them. In order to reduce the number of database pictures being matched by a user query, we also provide two suggestions to help enhance the effectiveness of image retrieval at the additional time cost.

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“…For three-dimensional pictures, representations such as the octree [18,22] were developed, and an extension of the 2D string to three dimensions was suggested in [12], and a unified approach to iconic indexing for 2D and 3D pictures was then proposed by Costagliola et al [14]. Other methods on image representation and retrieval can be found in the literature (see, e.g., [4,16,17]). …”

Section: Introductionmentioning

confidence: 99%

On Completeness of Reasoning about Planar Spatial Relationships in Pictorial Retrieval Systems

Yau

Zhang²

2004

Communications in Information and Systems

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Abstract. In this paper we consider the completeness problem of reasoning about planar spatial relationships in pictorial retrieval systems. We define a large class of two-dimensional scenes, the extended pseudo-symbolic pictures. The existing rule system R is proved to be complete for (extended) pseudo-symbolic pictures. We also introduce a new iconic indexing, the (extended) pseudo-2D string representation, for them. The (extended) pseudo-2D string has the good properties of the 2D string. It is unambiguous, like the augmented 2D string, and has a compact form suitable for image retrieval. We then present efficient algorithms to determine whether a given planar picture is (extended) pseudo-symbolic or not, and if it is, these algorithms also return its (extended) pseudo-2D string representation. Picture retrieval by (extended) pseudo-2D strings is also discussed.

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<title>Content-based indexing technique using relative geometry features</title>

Cited by 34 publications

References 0 publications

Development of an Image Retrieval Model for Biomedical Image Databases

Development of an Image Retrieval Model for Biomedical Image Databases

A Stepwise Approximation of Intractable Spatial Constraints in Image Queries

On Completeness of Reasoning about Planar Spatial Relationships in Pictorial Retrieval Systems

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