Proceedings ArticleDOI
Rapid Texture Identification
Kenneth I. Laws
- Vol. 0238, pp 376-381
TLDR
In this article, the texture energy approach requires only a few convolutions with small (typically 5x5) integer coefficient masks, followed by a moving-window absolute average operation.Abstract:
A method is presented for classifying each pixel of a textured image, and thus for segmenting the scene. The "texture energy" approach requires only a few convolutions with small (typically 5x5) integer coefficient masks, followed by a moving-window absolute average operation. Normalization by the local mean and standard deviation eliminates the need for histogram equalization. Rotation-invariance can also be achieved by using averages of the texture energy features. The convolution masks are separable, and can be implemented with 1-dimensional (vertical and horizontal) or multipass 3x3 convolutions. Special techniques permit rapid processing on general-purpose digital computers.read more
Citations
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Book ChapterDOI
Determine the Composition of Honeybee Pollen by Texture Classification
TL;DR: An automatic methodology to discriminate pollen loads of various genus based on texture classification is presented, which consists of three steps: after selection non-blurred regions of interest (ROIs) in the original image, a texture feature vector for each ROI is calculated, which is used to discriminate between pollen types.
Journal ArticleDOI
Multiple feature set with feature selection for anomaly search in videos using hybrid classification
A. Srinivasan,V. K. Gnanavel +1 more
TL;DR: Results show that MFS-HC provides better results than other approaches to detect anomalies in crowded scenes, compared with other approaches.
Proceedings ArticleDOI
Combined texture features for improved classification of suspicious areas in autofluorescence bronchoscopy
Panagiotis Bountris,Afroditi Apostolou,Maria Haritou,Elisavet Passalidou,Dimitris Koutsouris +4 more
TL;DR: An intelligent computing system based on combined texture features, feature selection methods and classification models is presented, for improved classification of suspicious areas of the bronchial mucosa, in order to decrease the rate of FPFs, to increase the specificity and sensitivity of AFB and enhance the overall diagnostic value of the AFB method.
Dissertation
Textural Measurements for Retinal Image Analysis
TL;DR: The preliminary results on using BRIEF as texture measurement for retinal image analysis are encouraging and demonstrate that it has the potential to be used in retina image analysis.
Proceedings ArticleDOI
Automated wear label assessment in carpets by using local binary pattern statistics on depth and intensity images
TL;DR: In this article, the authors presented an automated method for assessing carpet wear based on image analysis, where depth and intensity information were captured from eight types of carpet samples and the results showed that the method correctly assigned wear labels from 1 to 5 in steps of 1 for six of the eight carpet types.
References
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Journal ArticleDOI
Textural Features for Image Classification
TL;DR: These results indicate that the easily computable textural features based on gray-tone spatial dependancies probably have a general applicability for a wide variety of image-classification applications.
ReportDOI
Textured Image Segmentation
TL;DR: In this article, texture energy is measured by filtering with small masks, typically 5x5, then with a moving-window average of the absolute image values, leading to a simple class of texture energy transforms, which perform better than any of the preceding methods.