• Journal of Institute of Control, Robotics and Systems
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• v.9 no.2
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• pp.131-139
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• 2003

Shape descriptors play an important role in systems for object recognition, retrieval, registration, and analysis. Seven well-known descriptors including MPEG-7 visual descriptors arebriefly reviewed and a new robust pattern recognition descriptor is proposed. Performance comparison among descriptors are presented. Experiments show that the newly proposed descriptor yields better performance results than Fourier, invariant moment, and edge histogram descriptors.

• Journal of Information Processing Systems
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• v.16 no.2
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• pp.343-359
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• 2020

In this paper, a new algorithm is proposed for three-dimensional (3D) shape recognition using local features of model views and its sparse representation. The algorithm starts with the normalization of 3D models and the extraction of 2D views from uniformly distributed viewpoints. Consequently, the 2D views are stacked over each other to from view cubes. The algorithm employs the descriptors of 3D local features in the view cubes after applying Gabor filters in various directions as the initial features for 3D shape recognition. In the training stage, we store some 3D local features to build the prototype dictionary of local features. To extract an intermediate feature vector, we measure the similarity between the local descriptors of a shape model and the local features of the prototype dictionary. We represent the intermediate feature vectors of 3D models in the sparse domain to obtain the final descriptors of the models. Finally, support vector machine classifiers are used to recognize the 3D models. Experimental results using the Princeton Shape Benchmark database showed the average recognition rate of 89.7% using 20 views. We compared the proposed approach with state-of-the-art approaches and the results showed the effectiveness of the proposed algorithm.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.50 no.1
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• pp.60-66
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• 2005

Pod shape of twenty soybean (Glycine max L. Merrill) genotypes was evaluated quantitatively by image analysis using elliptic Fourier descriptors and their principal components. The closed contour of each pod projection was extracted, and 80 elliptic Fourier coefficients were calculated for each contour. The Fourier coefficients were standardized so that they were invariant of size, rotation, shift, and chain code starting point. Then, the principal components on the standardized Fourier coefficients were evaluated. The cumulative contribution at the fifth principal component was higher than $95\%$, indicating that the first, second, third, fourth, and fifth principal components represented the aspect ratio of the pod, the location of the pod centroid, the sharpness of the two pod tips and the roundness of the base in the pod contour, respectively. Analysis of variance revealed significant genotypic differences in these principal components and seed number per pod. As the principal components for pod shape varied continuously, pod shape might be controlled by polygenes. It was concluded that principal component scores based on elliptic Fourier descriptors yield seemed to be useful in quantitative parameters not only for evaluating soybean pod shape in a soybean breeding program but also for describing pod shape for evaluating soybean germplasm.

• Journal of Intelligence and Information Systems
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• v.15 no.4
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• pp.53-64
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• 2009

This paper presents a performance evaluation of shape descriptors for gait analysis in case of silhouette sequence images. We used moment descriptors(MD), Fourier descriptors(FD) and Zernike descriptors(ZD) as a shape descriptor. To evaluate their performance, we firstly defined the performance index, that is, AI(asymmetry index) and PI(periodic index) based on the periodic property of the gait images. This is why they are represented by periodic parameters due to periodic gait images. This index means that how the shape is represented periodically. According to these indexes, we evaluated the data sets with periodic images, downloaded from internet. The results showed that Zernike descriptors had better performance of AI = 1.09 and PI = 2.21 than others. And in case of FD and ZD, it's efficient to implement the gait analysis with 5~10 parameters.

• Water Engineering Research
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• v.6 no.2
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• pp.91-99
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• 2005

One of the most important factors for estimating a flood runoff from streams is the lag time. It is well known that the lag time is affected by the morphometric properties of basin which can be expressed by catchment shape descriptors. In this paper, the notion of the geometric characteristics of an equivalent ellipse proposed by Moussa(2003) was applied for calculating the lag time of geomorphologic instantaneous unit hydrograph(GIUH) at a basin outlet. The lag time was obtained from the observed data of rainfall and runoff by using the method of moments and the procedure based on geomorphology was used for GIUH. The relationships between the basin morphometric properties and the hydrological response were discussed based on application to 3 catchments in Korea. Additionally, the shapes of equivalent ellipse were examined how they are transformed from upstream area to downstream one. As a result, the relationship between the lag time and descriptors was shown to be close, and the shape of ellipse was presented to approach a circle along the river downwards. These results may be expanded to the estimation of hydrological response of ungauged catchment.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.279-286
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• 2000

The objective of this research is to detect the papaya fruits on tree in an orchard. The detection of papaya on natural background is difficult because colors of fruits and background such as leaves are similarly green. We cannot separate it from leaves by color information. Therefore, this research will use shape information instead. First, we detect an interested object by detecting its boundary using edge detection technique. However, the edge detection will detect every objects boundary in the image. Therefore, shape description technique will be used to describe which one is the interested object boundary. The good shape description should be invariant in scaling, rotating, and translating. The successful concept is to use Fourier series, which is called "Fourier Descriptors". Elliptic Fourier Descriptors can completely represent any shape, which is selected to describe the shape of papaya. From the edge detection image, it takes a long time to match every boundary directly. The pre-processing task will reduce non-papaya edge to speed up matching time. The deformable template is used to optimize the matching. Then, clustering the similar shapes by the distance between each centroid, papaya can be completely detected from the background.

• Journal of KIISE:Software and Applications
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• v.34 no.1
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• pp.1-10
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• 2007

This paper proposes a new indexing mechanism for MPEG-7 visual descriptors, especially Dominant Color and Contour Shape descriptors, that guarantees an efficient similarity search for the multimedia database whose visual meta-data are represented with MPEG-7. Since the similarity metric used in the Dominant Color descriptor is based on Gaussian mixture model, the descriptor itself could be transform into a color histogram in which the distribution of the color values follows the Gauss distribution. Then, the transformed Dominant Color descriptor (i.e., the color histogram) is indexed in the proposed indexing mechanism. For the indexing of Contour Shape descriptor, we have used a two-pass algorithm. That is, in the first pass, since the similarity of two shapes could be roughly measured with the global parameters such as eccentricity and circularity used in Contour shape descriptor, the dissimilar image objects could be excluded with these global parameters first. Then, the similarities between the query and remaining image objects are measured with the peak parameters of Contour Shape descriptor. This two-pass approach helps to reduce the computational resources to measure the similarity of image objects using Contour Shape descriptor. This paper also proposes two integration schemes of visual descriptors for an efficient retrieval of multimedia database. The one is to use the weight of descriptor as a yardstick to determine the number of selected similar image objects with respect to that descriptor, and the other is to use the weight as the degree of importance of the descriptor in the global similarity measurement. Experimental results show that the proposed indexing and integration schemes produce a remarkable speed-up comparing to the exact similarity search, although there are some losses in the accuracy because of the approximated computation in indexing. The proposed schemes could be used to build a multimedia database represented in MPEG-7 that guarantees an efficient retrieval.

• Journal of Broadcast Engineering
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• v.13 no.6
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• pp.962-965
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• 2008

2-D shape descriptors, which are vectors representing characteristics of shapes, enable comparison and classification of shapes and are mainly applied to image and 3-D model retrieval. Existing descriptors have limitations that they only describe shapes of single closed contours or lack in precision, making it difficult to be applied to shapes with multiple contours. Therefore, in this paper, we propose a new shape descriptor called Multi-Curvature-Scale Space that can be applied to shapes with multiple contours. Specifically, we represent the topology of the sub-contours in the multi-contour along with Curvature-Scale Space descriptors to represent the shapes of each sub-contours. Also, by allowing the weight of each component to be controlled when computing the distance between descriptors the weight, we deal with ambiguities in measuring similarity between shapes. Results of various experiments that prove the effectiveness of proposed descriptor are presented.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1998.10a
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• pp.115-123
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• 1998

The morphological analysis of wear particle is a very effective means for machine condition monitoring and fault diagnosis. In order to describe morphology of various wear particle, the wear test was carried out under different experimental conditions. And fractal descriptors was applied to boundary and surface of wear particle with image processing system. These descriptors to analyze shape and surface wear particle are shape fractal dimension and surface fractal dimension. The shape fractal dimension can be derived from the boundary profile and surface fractal dimension can be determined by sum of intensity difference of surface pixel. The morphology of wear particles can be effectively obtained by two fractal dimensions.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1531-1534
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• 2002

Shape description and its corresponding matching algorithm is one of the main concerns in MPEG-7. In this paper, a new method is proposed for shape registration of 2D objects for MPEG-7 Shapes are recognized using the Hu statistical moments in frequency domain. The Hu moments are moment-based descriptors of planar shapes, which are invariant under general translation, rotational, scaling, and reflection transformation. The image is transformed into frequency domain using Fourier Transform. Annular and radial wedge distributions fur the power spectra are extracted. Different statistical features (Hu moments) are found f3r the power spectrum of each selected transformed individual feature. The Euclidean distance of the extracted moment descriptors of the features are found with respect to the shapes in the database. The minimum Euclidean distance is the candidate for the matched shape. The simulation results are performed on the test shapes of MPEG-7.