Rotation Invariant Co-occurrence among Adjacent LBPs

نویسندگان

  • Ryusuke Nosaka
  • Chendra Hadi Suryanto
  • Kazuhiro Fukui
چکیده

In this paper, we propose a new type of local binary pattern (LBP)-based feature, called Rotation Invariant Co-occurrence among adjacent LBPs (RIC-LBP), which simultaneously has characteristics of rotation invariance and a high descriptive ability. LBP was originally designed as a texture description for a local region, called a micropattern, and has been extended to various types of LBP-based features. In this paper, we focus on Co-occurrence among Adjacent LBPs (CoALBP). Our proposed feature is enabled by introducing the concept of rotation equivalence class to CoALBP. The validity of the proposed feature is clearly demonstrated through comparisons with various state-of-the-art LBP-based features in experiments using two public datasets, namely, the HEp-2 cell dataset and the UIUC texture database.

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

Feature Extraction Based on Co-occurrence of Adjacent Local Binary Patterns

In this paper, we propose a new image feature based on spatial co-occurrence among micropatterns, where each micropattern is represented by a Local Binary Pattern (LBP). In conventional LBP-based features such as LBP histograms, all the LBPs of micropatterns in the image are packed into a single histogram. Doing so discards important information concerning spatial relations among the LBPs, even...

متن کامل

Analysis of Virus Textures in Transmission Electron Microscopy Images

In this paper we propose an ensemble of texture descriptors for analyzing virus textures in transmission electron microscopy images. Specifically, we present several novel multi-quinary (MQ) codings of local binary pattern (LBP) variants: the MQ version of the dense LBP, the MQ version of the rotation invariant co-occurrence among adjacent LBPs, and the MQ version of the LBP histogram Fourier. ...

متن کامل

Rotation Invariant Texture Classification Using Texton Co-occurrence Matrix Derived from Texture Orientation 5.1 Rotation Invariant Texture Classification Based on Texton Co-occurrence Matrix

In the previous chapter, an integrated approach for texture classification using ILCLBP-T is proposed. In continuation to that, the present chapter derived a new co-occurrence matrix based on textons and texture orientation for rotation invariant texture classification of 2D images. The new co-occurrence matrix is called as Texton and Texture Orientation Co-occurrence Matrix (T&TO-CM). The Co-o...

متن کامل

Texture-based Fuzzy System for Rotation-invariant Classification of Aerial Orthoimage Regions

Orthoimages are aerial images where feature displacements and scale variations have been removed. This type of images is widely used to calculate areas, determine land cover and land use, among others. This paper introduces a rotation-invariant classification model for three common orthoimage regions: city, sea and forest areas, using only texture information (without color information). Our cl...

متن کامل

Rotation invariant co-occurrence features based on digital circles and discrete Fourier transform

Texture classification co-occurrence matrices rotation invariance digital circles discrete Fourier transform. Grey-level co-occurrence matrices (GLCM) have been on the scene for almost forty years and continue to be widely used today. In this paper we present a method to improve accuracy and robustness against rotation of GLCM features for image classification. In our approach co-occurrences ar...

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 2012