Structural filtering with texture feature-based interaction maps: fast algorithm and applications

نویسنده

  • Dmitry Chetverikov
چکیده

We have recently introduced a new tool for texture analysis called feature based interaction map (FBIM). The FBIM approach can be efficiently used to assess fundamental structural properties of textures such as anisotropy, symmetry, orientation and regularity [4]. It has been demonstrated [5] that the FBIM is suitable for rotation-invariant texture classification of patterns with regular, weak regular, or linear structure. In this paper, we show how the interaction map can be applied as a structural filter for segmentation, detection of textured objects and texture defects, analysis of oriented structures and shape-from-texture. The power of the FBIM filter is in its unique capability to grasp the structure of pixel interactions typical for a given texture pattern. To efficiently use this capability, we propose a fast running implementation of the FBIM algorithm and present pilot experimental results demonstrating the potential of the FBIM approach in diverse tasks and applications. 1

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Fast SFFS-Based Algorithm for Feature Selection in Biomedical Datasets

Biomedical datasets usually include a large number of features relative to the number of samples. However, some data dimensions may be less relevant or even irrelevant to the output class. Selection of an optimal subset of features is critical, not only to reduce the processing cost but also to improve the classification results. To this end, this paper presents a hybrid method of filter and wr...

متن کامل

Online Streaming Feature Selection Using Geometric Series of the Adjacency Matrix of Features

Feature Selection (FS) is an important pre-processing step in machine learning and data mining. All the traditional feature selection methods assume that the entire feature space is available from the beginning. However, online streaming features (OSF) are an integral part of many real-world applications. In OSF, the number of training examples is fixed while the number of features grows with t...

متن کامل

On the use of Textural Features and Neural Networks for Leaf Recognition

for recognizing various types of plants, so automatic image recognition algorithms can extract to classify plant species and apply these features. Fast and accurate recognition of plants can have a significant impact on biodiversity management and increasing the effectiveness of the studies in this regard. These automatic methods have involved the development of recognition techniques and digi...

متن کامل

A Fast Localization and Feature Extraction Method Based on Wavelet Transform in Iris Recognition

With an increasing emphasis on security, automated personal identification based on biometrics has been receiving extensive attention. Iris recognition, as an emerging biometric recognition approach, is becoming a very active topic in both research and practical applications. In general, a typical iris recognition system includes iris imaging, iris liveness detection, and recognition. This rese...

متن کامل

Second-Order Statistical Texture Representation of Asphalt Pavement Distress Images Based on Local Binary Pattern in Spatial and Wavelet Domain

Assessment of pavement distresses is one of the important parts of pavement management systems to adopt the most effective road maintenance strategy. In the last decade, extensive studies have been done to develop automated systems for pavement distress processing based on machine vision techniques. One of the most important structural components of computer vision is the feature extraction met...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1996