A graph-based relevance feedback mechanism in content-based image retrieval

نویسندگان

  • Malay Kumar Kundu
  • Manish Chowdhury
  • Samuel Rota Bulò
چکیده

Content-Based Image Retrieval (CBIR) is an important problem in the domain of digital data management. There is indeed a growing availability of images, but unfortunately the traditional metadata-based search systems are unable to properly exploit their visual information content. In this article we introduce a novel CBIR scheme that abstracts each image in the database in terms of statistical features computed using the Multi-scale Geometric Analysis (MGA) of Non-subsampled Contourlet Transform (NSCT). Noise resilience is one of the main advantages of this feature representation. To improve the retrieval performance and reduce the semantic gap, our system incorporates a Relevance Feedback (RF) mechanism that uses a graphtheoretic approach to rank the images in accordance with the user’s feedback. First, a graph of images is constructed with edges reflecting the similarity of pairs of images with respect to the proposed feature representation. Then, images are ranked at each feedback round in terms of the probability that a random walk on this graph reaches an image tagged as relevant by the user before hitting a non-relevant one. Experimental analyses on three different databases show the effectiveness of our algorithm compared to state-of-theart approaches in particular when the images are corrupted with different types of noise. ✩This work is supported by internal academic project fund of Machine Intelligence Unit, Indian Statistical Institute, 203 B. T. Road, Kolkata-108. ∗Corresponding author: Tel.: +91-33-2575-3100; Fax: +91-33-2578-3357 Email addresses: [email protected] (Malay Kumar Kundu), [email protected] (Manish Chowdhury), [email protected] (Samuel Rota Bulò) Preprint submitted to Knowledge Based System July 18, 2014

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

Document Image Retrieval Based on Keyword Spotting Using Relevance Feedback

Keyword Spotting is a well-known method in document image retrieval. In this method, Search in document images is based on query word image. In this Paper, an approach for document image retrieval based on keyword spotting has been proposed. In proposed method, a framework using relevance feedback is presented. Relevance feedback, an interactive and efficient method is used in this paper to imp...

متن کامل

بازیابی تعاملی تصاویر طبیعت با بهره گیری از یادگیری چند نمونه ای

Content-based image retrieval (CBIR) has received considerable research interest in the recent years. The basic problem in CBIR is the semantic gap between the high-level image semantics and the low-level image features. Region-based image retrieval and learning from user interaction through relevance feedback are two main approaches to solving this problem. Recently, the research in integra...

متن کامل

Effective Region-based Relevance Feedback for Interactive Content-based Image Retrieval

This paper proposes an effective framework for interactive region-based image retrieval. By utilizing fuzzy coarse segmentation and the graph structure for representing each image, the retrieval process was performed by measuring the image similarity according to the graph similarity. To assess the similarity between two graphs, fuzzy inter relations among regions feature vectors and spatial di...

متن کامل

A Scalable Graph-Based Semi-Supervised Ranking System for Content-Based Image Retrieval

The authors propose a scalable graph-based semi-supervised ranking system for image retrieval. This system exploits the synergism between relevance feedback based transductive short-term learning and semantic feature-based long-term learning to improve retrieval performance. Active learning is applied to build a dynamic feedback log to extract semantic features of images. Two-layer manifold gra...

متن کامل

Semiautomatic Image Retrieval Using the High Level Semantic Labels

Content-based image retrieval and text-based image retrieval are two fundamental approaches in the field of image retrieval. The challenges related to each of these approaches, guide the researchers to use combining approaches and semi-automatic retrieval using the user interaction in the retrieval cycle. Hence, in this paper, an image retrieval system is introduced that provided two kind of qu...

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:
  • Knowl.-Based Syst.

دوره 73  شماره 

صفحات  -

تاریخ انتشار 2015