Active Learning Methods for Interactive Image Retrieval

Abstract:

Active learning methods have been considered with increased interest in the statistical learning community. Initially developed within a classification framework, a lot of extensions are now being proposed to handle multimedia applications. This paper provides algorithms within a statistical framework to extend active learning for online content-based image retrieval (CBIR). The classification framework is presented with experiments to compare several powerful clas ....etc

[:=Read Full Message Here=:]

To get full information or details of content based image retrieval please have a look on the pages

http://seminarsprojects.net/Thread-content-based-image-retrieval-cbir-system?pid=116513&mode=linear

http://seminarsprojects.net/Thread-content-based-image-retrieval-cbir-system?pid=56865

http://seminarsprojects.net/Thread-content-based-image-retrieval-cbir-system?pid=27498&mode=threaded

http://seminarsprojects.net/Thread-content-based-image-retrieval-cbir-system

http://seminarsprojects.net/Thread-cbir-content-based-image-retrieval-using-shap ....etc

[:=Read Full Message Here=:]

Grayscale Image Retrieval using DCT on Row mean,
Column mean and Combination



Abstract

Today in the age of information explosion, how to search appropriate data from huge information
pool has become vital issue. Images have giant share in this information pool. Because of easy
availability of imaging devices, millions of images are being added to image pool every day. Image
retrieval deals with searching relevant images from large image database. The paper presents novel
image retrieval techniques bas ....etc

[:=Read Full Message Here=:]

request:sir please send me full information about this project and ppt if possible what are the active methods for interactive image retrieval

my project abstract:
title:active learning methods for interactive image retrieval

RGB BASED IMAGE SEARCH ENGINE

Abstract:

Active learning methods have been considered with increased interest in the statistical learning community. Initially developed within a classification framework, a lot of extensions are now being proposed to handle multim ....etc

[:=Read Full Message Here=:]

hello, friend I need code for texture..my project is IP based..image retrieving, i wrote the code for color histogram and edge detection..but getting difficulties in texture..i will b really much thankful to you if you provide me code for texture..comparing the image and distinguishing based on texture..plz..thanks in advance :) ....etc

[:=Read Full Message Here=:]

1. INTRODUCTION
There are number of existing retrieval techniques for images. Text based techniques are the most
commonly used. In text-based systems the images are first annotated by text and then text indexing and
retrieval techniques are used. Content based retrieval techniques followed the text-based system where
in low level image features like color, texture etc. are used to retrieve similar images. In text-based
systems, manual annotation poses a ....etc

[:=Read Full Message Here=:]

Abstract

Content-based image retrieval (CBIR), also known as query by image content (QBIC) and content-based visual information retrieval (CBVIR) is the application of computer vision techniques to the image retrieval problem, that is, the problem of searching for digital images in large databases (see this survey for a recent scientific overview of the CBIR field). Content-based image retrieval is opposed to traditional concept-based approaches (see Concept-based image indexing).Content-based means that the search analyzes the contents of t ....etc

[:=Read Full Message Here=:]

to get information about the topic supervised learning of semantic classes for image annotation and retrieval full report ppt and related topic refer the page link bellow
http://seminarsprojects.net/Thread-supervised-learning-of-semantic-classes-for-image-anotation-and-retrieval ....etc

[:=Read Full Message Here=:]

Abstract A probabilistic formulation for semantic image annotation and retrieval is proposed. Annotation and retrieval are posed as
classification problems where each class is defined as the group of database images labeled with a common semantic label. It is
shown that, by establishing this one-to-one correspondence between semantic labels and semantic classes, a minimum probability of
error annotation and retrieval are feasible with algorithms that are 1) conceptually simple, 2) computationally efficient, and 3) do not
require prior sema ....etc

[:=Read Full Message Here=:]

i need the code for sparse color interest points for imsge retrivel ....etc

[:=Read Full Message Here=:]