D. Ballard. Generalized hough transform to detect arbitrary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence, 13(2):111--122, 1981.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....knowledge about the world, usually an exhaustive search of the image must be performed to identify the object. The generalized Hough transform (GHT) is a technique to perform this search by discretizing all possible transformations between object and image space and testing them individually [2, 28]. The percentage of resulting matches between object and image features are interpreted as the likelihood for a respective transformation to be correct. However, to attain reliable GHT detection results, a large number of object features and a high resolution Hough table is required [8] resulting ....

D. Ballard. Generalized hough transform to detect arbitrary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence, 13(2):111--122, 1981.

....matching, maximum likelihood, branch andbound 1 Introduction Matching of points or other geometric primitives under geometric transformations is an important problem in many applications, including computer vision and robotics. Early work on matching has included the Generalized Hough Transform[2], heuristic search[8] and a variety of other techniques. Over the last decade, branch and bound techniques have become increasingly popular for geometric matching problems Such techniques work by recursively subdividing the space of parameters of the geometric transformations under consideration ....

D. H. Ballard. Generalized hough transform to detect arbitrary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence, 13(2):111--122, 1981.

....the value of pixel p j (x; y) Since all edge and outline pixels have equal weight, 1) represents a binary convolution consisting only of incrementing memory addresses which can be implemented very efficiently. The convolution result H j resembles the edge image s generalized Hough transform [2, 7, 6] for outline L pose j (Fig.2c) To find the best matching position for outline L pose j in the image, the coordinates in the Hough transform with the highest pixel value p max j ( x j ; y j ) are sought. Since image edges as well as silhouette outlines are represented by one pixel wide ....

D. Ballard. Generalized hough transform to detect arbitrary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence, 13(2):111--122, 1981.

....geometry is the development of exact, provably correct and efficient solutions to geometric problems. First some related work is mentioned in the next subsection. 1. 1 Related work Matching has been approached in a number of ways, including tree pruning [55] the generalized Hough transform [8] or pose clustering [51] geometric hashing [59] the alignment method [27] statistics [40] deformable templates [50] relaxation labeling [44] Fourier descriptors [35] wavelet transform [31] curvature scale space [36] and neural networks [21] The following subsections treat a few methods ....

....assumed to be the transformation between the two shapes. The complexity of matching a single query set of # points is ####. There are several variations of this basic method, such as balancing the hashing table, or avoiding taking all possible ### # ## tuples. The generalized Hough transform [8], or pose clustering [51] is also a voting scheme. Here, affine transformations are represented by six coefficients. The quantized transformation space is represented as a six dimensional table. Now for each triplet of points in one set, and each triplet of points from the other set, compute the ....

D. H. Ballard. Generalized Hough transform to detect arbitrary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence, 13(2):111--122, 1981.

....pixels) and edge separation from the grey level image. Finally, if there is sucient similarity in their texture between the query object and the area in the database image where the supposed similar object was identi ed, a shape veri cation based on the Generalized Hough Transform is performed [Bal81] Result presentation The user can choose the number of rows and columns of the displayed images grid. By clicking on a thumbnail image the user can see some color and texture characteristics of the image (color percentage and layout, texture layout) 8 Chabot Developer Department of Computer ....

D. H. Ballard. Generalized Hough transform to detect arbitrary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence, 13(2):111-122, 1981.

....the dissimilarity measure. Figure 2: Fingerprint matching. Figure 3: Query hieroglyph (left) and hieroglyphs retrieved from database, from [VV99] 2 Approaches Matching has been approached in a number of ways, including tree pruning [Ume93] the generalized Hough transform or pose clustering [Bal81] Sto87] geometric hashing [WR97] the alignment method [HU87] statistics [Sma96] deformable templates [SP95] relaxation labeling [RR80] Fourier descriptors [Lon98] wavelet transform [JFS95] curvature scale space [MAK96] and neural networks [Gol95] Without being complete, in the ....

....be the transformation between the query and the target. The complexity of matching a single query set of n points is O(n) There are several variations of this basic method, such as balancing the hashing table, or avoiding taking all possible O(n 3 ) 3 tuples. The generalized Hough transform [Bal81] or pose clustering [Sto87] is also a voting scheme. Here, a ne transformations are represented by six coe cients. The quantized transformation space is represented as a six dimensional table. Now for each triplet of points in the query set, and each triplet of points from the target set, ....

D. H. Ballard. Generalized Hough transform to detect arbitrary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence, 13(2):111-122, 1981.

....a certain criterion is satisfied. Although a number of modified versions of this algorithm have been proposed to reduce the matching complexity [69] these algorithms are inherently slow because of their iterative nature. The generalized Hough transform based approach to point pattern matching [6, 67] converts point pattern matching to a problem of detecting peaks in the Hough space of transformation parameters. It discretizes the parameter space and accumulates evidence in the discretized space by deriving transformation parameters that relate two point patterns using a substructure or ....

D. H. Ballard, Generalized Hough Transform to Detect Arbitrary Patterns, IEEE Transactions on PAMI, Vol. 3, No. 2, pp. 111-122, 1981.

.... matches while eliminating portions of the search space (Baird, 1984; Grimson and Lozano Perez, 1987; Umeyama, 1993) The generalized Hough transform requires the division of the parameter space of possible poses into discrete bins wherein good matches are registered as votes in the appropriate bin (Ballard, 1981; Stockman, 1987) Geometric hashing is another voting scheme where discrete bins are created for the possible bases that can be used to represent the point sets (Lamdan et al. 1988; Hummel and Wolfson, 1988) In the alignment method (Ullman, 1989) each alignment feature (defined as a set of ....

Ballard, D. H. (1981). Generalized hough transform to detect arbitrary patterns. IEEE Trans.

....tree of possible matches while eliminating branches of the tree from consideration (Baird, 1984; Grimson and Lozano Perez, 1987; Umeyama, 1993) The generalized Hough transform divides the valid set of spatial mappings into discrete bins. Good matches are registered as votes in the appropriate bin (Ballard, 1981; Stockman, 1987) In geometric hashing, depending on the spatial mapping, a set of possible bases that can represent the point sets is generated. Then a voting based search is conducted to determine the point to point correspondences (Lamdan et al. 1988; Hummel and Wolfson, 1988) In the ....

Ballard, D. H. (1981). Generalized Hough transform to detect arbitrary patterns. IEEE Trans. Patt. Anal.

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D. Ballard. Generalized hough transform to detect arbitrary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence, 13(2):111--122, 1981.

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D. H. Ballard, "Generalized Hough Transform to Detect Arbitrary Patterns," IEEE Transactions on Pattern Analysis and Machine Intelligence 13(2), pp. 111--122, 1981.

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D. H. Ballard, "Generalized Hough Transform to Detect Arbitrary Patterns," IEEE Transactions on Pattern Analysis and Machine Intelligence 13(2), pp. 111--122, 1981.

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D. Ballard. Generalized Hough transform to detect arbitrary patterns. IEEE PAMI, 12:111--122, 1981.

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D. H. Ballard, "Generalized hough transform to detect arbitrary patterns," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 13, no. 2, pp. 111--122, 1981.

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D.H.Ballard, "Generalized Hough transform to detect arbitrary patterns", IEEE Transaction on pattern Analysis and Machine Intelligence, 13(2): 111-122,1981.

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D. Ballard. Generalized hough transform to detect arbitrary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence, 13(2):111--122, 1981.

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D. Ballard. Generalized Hough Transforms to Detect Arbitrary Patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence, 13(2):111--122, 1981.

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D. H. Ballard, "Generalized Hough transform to detect arbitrary shapes", Pattern Recognition, 13(2):111-122, 1981.

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Ballard, D.: Generalized hough transform to detect arbitrary patterns. IEEE PAMI 12 (1981) 111--122

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