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Development of Feature Descriptor for Texture Classification
2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI), 2019Image classification strategies based on surfaces play an imperative part in different computer vision applications. The challenge exists in texture classification are rotation, illumination, scale and orientation changes. Our proposed method uses efficient features for texture classification that overcomes all the above challenges.
P. T. Vanathi +2 more
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Feature Selection and Heterogeneous Descriptors
2012While the focus in Chap. 5 was on descriptors that were made up of homogeneous features, the focus in this chapter is on descriptors that are composed of features of different types. Heterogeneous descriptors are created from a combination of various types of features as described in Chap. 4.
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Geodesic Invariant Feature: A Local Descriptor in Depth
IEEE Transactions on Image Processing, 2015Different from the photometric images, depth images resolve the distance ambiguity of the scene, while the properties, such as weak texture, high noise, and low resolution, may limit the representation ability of the well-developed descriptors, which are elaborately designed for the photometric images.
Quansen Sun +3 more
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A novel biologically inspired local feature descriptor
Biological Cybernetics, 2014Local feature descriptor is a fundamental representation for image patch which has been extensively used in many computer vision applications. In this paper, different from state-of-the-art features, a novel biologically inspired local descriptor (BILD) is proposed based on the visual information processing mechanism of ventral pathway in human brain ...
Tian Tian +4 more
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A Hybrid Image Feature Descriptor for Classification
2015 11th International Conference on Computational Intelligence and Security (CIS), 2015Feature extraction methods have an important role in image classification. In this paper, a hybrid texture feature descriptor is proposed by utilizing the attributes of two complementary features, PRICoLBP and LPQ. PRICoLBP performs well in the case of geometric and photometric variations however it does not properly express the local texture of an ...
Ping Guo, Hussian Dawood, Hassan Dawood
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On coding of images and SIFT feature descriptors
SPIE Proceedings, 2012We offer probabilistic interpretation of meaning of SIFT image features. This allows us to derive formulae connecting SIFT feature values to parameters of gradient distributions. We also study KL-distances between gradient distributions and establish their connections to values in SIFT descriptors.
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Active Descriptor Learning for Feature Matching
2019Feature descriptor extraction lies at the core of many computer vision tasks including image retrieval and registration. In this paper, we present an active learning method for extracting efficient features to be used in matching image patches. We train a Siamese deep neural network by optimizing a triplet loss function. We develop a more efficient and
Aziz Koçanaoğulları +1 more
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Local binary hexagonal extrema pattern (LBHXEP): a new feature descriptor for fake iris detection
The Visual Computer, 2020Rohit Agarwal, A. S. Jalal, K. V. Arya
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An Experimental Evaluation of Binary Feature Descriptors
2017Efficient and compact representation of local image patches in the form of features descriptors that are distinctive/robust as well as fast to compute and match is an essential and inevitable step for many computer vision applications. One category of these representations is the binary descriptors which have been shown to be successful alternatives ...
Guanghui Wang +4 more
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Region-based depth feature descriptor for saliency detection on light field
Multimedia tools and applications, 2020Xue Wang +3 more
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