Image retrieval based on micro-structure descriptor

نویسندگان

  • Guang-Hai Liu
  • Zuoyong Li
  • Lei Zhang
  • Yong Xu
چکیده

This paper presents a simple yet efficient image retrieval approach by proposing a new image feature detector and descriptor, namely the micro-structure descriptor (MSD). The micro-structures are defined based on an edge orientation similarity, and the MSD is built based on the underlying colors in microstructures with similar edge orientation. With micro-structures serving as a bridge, the MSD extracts features by simulating human early visual processing and it effectively integrates color, texture, shape and color layout information as a whole for image retrieval. The proposed MSD algorithm has high indexing performance and low dimensionality. Specifically, it has only 72 dimensions for full color images, and hence it is very efficient for image retrieval. The proposed method is extensively tested on Corel datasets with 15,000 natural images. The results demonstrate that it is much more efficient and effective than representative feature descriptors, such as Gabor features and multi-textons histogram, for image retrieval. Crown Copyright & 2011 Published by Elsevier Ltd. All rights reserved.

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

A Novel Image Structural Similarity Index Considering Image Content Detectability Using Maximally Stable Extremal Region Descriptor

The image content detectability and image structure preservation are closely related concepts with undeniable role in image quality assessment. However, the most attention of image quality studies has been paid to image structure evaluation, few of them focused on image content detectability. Examining the image structure was firstly introduced and assessed in Structural SIMilarity (SSIM) measu...

متن کامل

Image Retrieval System with User Relevance Feedback

Image retrieval approach by proposing a new image feature detector and descriptor, namely the micro-structure descriptor (MSD). We present a computational model of creative design based on collaborative interactive genetic algorithms. This Paper test our model on floor planning. This Paper guide the evolution of floorplan based on subjective and objective criteria. The subjective criteria consi...

متن کامل

Performance Analysis of Saliency Structure Model in Image Retrieval

A novel mechanism to simulate visual attention mechanisms for content-based image retrieval, based on saliency structure histogram method was proposed in this paper. In CBIR, images are indexed by their visual content, such as color, texture, shapes. A color volume with edge information together is used to detect saliency regions. The texture image features, such as energy, inverse difference m...

متن کامل

A Novel Local Structure Descriptor for Color Image Retrieval

A novel local structure descriptor (LSD) for color image retrieval is proposed in this paper. Local structures are defined based on a similarity of edge orientation, and LSD is constructed using the underlying colors in local structures with similar edge direction. LSD can effectively combine color, texture and shape as a whole for image retrieval. LSH integrates the advantages of both statisti...

متن کامل

Image Retrieval Using Multi Texton Co-occurrence Descriptor

Image retrieval system is one of a challenging topic and is not yet finalized. A number of features extraction methods has been proposed, for example Gray Level CoOccurrence Matrix (GLCM), Texton Co-Occurrence Histogram (TCM), Multi Texton Histogram (MTH), Micro Stucture Descriptor (MSD), Enhanced Micro Structure Descriptor (EMSD) and Color difference Histogram (CDH). However, the precision rat...

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:
  • Pattern Recognition

دوره 44  شماره 

صفحات  -

تاریخ انتشار 2011