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 …

Huge number of images is available on the internet. Efficient and effective retrieval system is
needed to retrieve these images by the contents or features of the images like color, texture …

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 …

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 …

The efficient feature extraction and effective similar image retrieval are important steps for
effective content-based image retrieval (CBIR) system. The extraction of features in …

This paper presents a novel image feature representation method, called local texture-
based color histogram (LTCH), for content-based image retrieval. The LTCH can describe …

Content-Based Image Retrieval (CBIR) is the process of searching digital images in a large
database based on features, such as colour, texture and shape of a given query image. As …

Content-based image retrieval (CBIR) has drawn substantial research and many traditional
CBIR systems search digital images in a large database based on features, such as color …

Content based image retrieval (CBIR) systems in pixel domain use low-level features such
as color, texture, and shape for image queries. Extracting these features and comparing it …

This paper proposes a new simple method of Discrete Cosine Transform (DCT) feature
extraction that is used to accelerate the speed and decrease the storage needed in the …