Results 281 to 290 of about 49,054 (309)
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2019
This chapter focuses on another image feature called the texture feature. Two types of texture feature methods are discussed: traditional spatial methods and contemporary spectral methods. The chapter first introduces four spatial or handcrafted methods including Tamura, GLCM, MRF, and FD.
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This chapter focuses on another image feature called the texture feature. Two types of texture feature methods are discussed: traditional spatial methods and contemporary spectral methods. The chapter first introduces four spatial or handcrafted methods including Tamura, GLCM, MRF, and FD.
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Selection of Gabor filters for improved texture feature extraction
2010 IEEE International Conference on Image Processing, 2010Texture feature has been widely used in object recognition, image content analysis and many others. Among various approaches to texture feature extraction, Gabor filter has emerged as one of the most popular ones. Gabor filter-based feature extractor is in fact a Gabor filter bank defined by its parameters including frequencies, orientations and smooth
Weitao Li +3 more
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Level curve tracking algorithm for textural feature extraction
Proceedings 15th International Conference on Pattern Recognition. ICPR-2000, 2002Topographic approaches are often used in the framework of texture characterization. More particularly, level curves proved to be interesting features to describe textures containing elongated patterns. Here, we provide an algorithm for level curve tracking based on a step by step propagation of a level set from a pixel to its neighbors.
Jean-Pierre Da Costa +2 more
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Texture extraction and segmentation via statistical geometric features
Proceedings of 3rd IEEE International Conference on Image Processing, 2002The statistical geometric features (SGF) are a new approach to texture analysis combining statistics with geometrical attributes to give a powerful discriminatory ability. The original scheme considered the approach in principal and did not address factors important to its eventual application, namely its implementation and the segmentation of texture ...
Ben S. Runnacles, Mark S. Nixon
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Dominant color and texture feature extraction for banknote discrimination
Journal of Electronic Imaging, 2017Banknote discrimination with image recognition technology is significant in many applications. The traditional methods based on image recognition only recognize the banknote denomination without discriminating the counterfeit banknote. To solve this problem, we propose a systematical banknote discrimination approach with the dominant color and texture ...
Junmin Wang, Yangyu Fan, Ning Li
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A Survey on Local Textural Patterns for Facial Feature Extraction
International Journal of Computer Vision and Image Processing, 2018Over the last two decades retrieving an accurate image has become a challenging task. Regardless, texture patterns address this problem by decreasing the significant gap between the actual image over the user expectation rather than other low-level features.
V. Uma Maheswari 0001 +2 more
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Robust feature extraction technique for texture image retrieval
IEEE International Conference on Image Processing 2005, 2005This paper proposes a novel texture feature extraction technique for texture image retrieval. The method is robust to geometric distortions as well as noise effect. The geometric distortions include rotation, scaling and translation modifications of textures. In the feature extracting process, log-polar transformed autocorrelation images are introduced
Zhuo Liu, Shigeo Wada
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Crowd Density Estimation Based on Texture Feature Extraction
Journal of Multimedia, 2013As we know, feature extraction has an important role in crowd density estimation. In our paper, we introduce a new texture feature called Tamura, which is usually used in image retrieval algorithms. On the other hand, the time consuming is another issue that must be considered, especially for the real-time application of the crowd density estimation ...
Bobo Wang +3 more
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Texture Feature Extraction and Selection for Classification of Images in a Sequence
2004This paper presents texture feature extraction and selection methods for on-line pattern classification evaluation. Feature selection for texture analysis plays a vital role in the field of image recognition. Despite many approaches done previously, this research is entirely different from them since it comes from the fundamental ideas of feature ...
Khin K. Win +5 more
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An analytical review of texture feature extraction approaches
International Journal of Computer Applications in Technology, 2021Mohammad Reza Keyvanpour +2 more
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