An effective Content-Based Image Retrieval (CBIR) system is based on efficient feature
extraction and accurate retrieval of similar images. Enhanced images by using proper filter …

Effective Content-Based Image Retrieval (CBIR) is based on efficient low level features
extraction for indexing and on effective query image matching with indexed images for …

The effective content-based image retrieval (CBIR) needs efficient extraction of low level
features like color, texture and shapes for indexing and fast query image matching with …

Texture gradient is a popular operation for extracting features used for content-based image
retrieval (CBIR) of texture images. It is useful for depicting gradient magnitude and direction …

In this paper we propose a new and efficient technique to retrieve images based on sum of
the values of Local Histogram and GLCM (Gray Level Co-occurrence Matrix) texture to …

Finding specific digital images from large resources has become an area of wide interest
nowadays. Among image retrieval approaches, text based retrieval is widely used as it has …

Content based image retrieval (CBIR) is an extrusive technique of retrieving the relevant
images from vast image archives by extracting their low level features. In this research …

Content-Based Image Retrieval (CBIR) allows automatically extracting target images
according to objective visual contents of the image itself. Content-based image retrieval has …

An innovative medical image retrieval is proposed to extract low-level image texture
features. These low level texture features were extracted directly using Modified Discrete …

The project proposes the image retrieval technique based on Gray Level Co-occurrence
Matrix (GLCM) and Shape features. The main target of Content-based Image Retrieval …