In this paper, we propose a novel image indexing and retrieval algorithm using local tetra
patterns (LTrPs) for content-based image retrieval (CBIR). The standard local binary pattern …

Feature detection, description and matching are essential components of various computer
vision applications, thus they have received a considerable attention in the last decades …

The Content Based Image retrieval (CBIR) is a very important for retrieving the most visual
relevant images from the large image database. The various low level features are extracted …

A new image feature description based on the local wavelet pattern (LWP) is proposed in
this paper to characterize the medical computer tomography (CT) images for content-based …

A new algorithm meant for content based image retrieval (CBIR) and object tracking
applications is presented in this paper. The local region of image is represented by local …

A real world problem of image retrieval and searching is considered in this paper. In modern
generation, managing images from a large storage medium is not a straightforward job …

A new content‐based image retrieval (CBIR) scheme is proposed based on the optimised
combination of the colour and texture features to enhance the image retrieval precision. This …

Nitrogen (N) content is an important basis for the precise management of wheat fields. The
application of unmanned aerial vehicles (UAVs) in agriculture provides an easier and faster …

Remote sensing scene objective recognition (RSSOR) plays a serious application value in
both military and civilian fields. Convolutional neural networks (CNNs) have greatly …

In this paper, a novel feature descriptor, local texton XOR patterns (LTxXORP) is proposed
for content-based image retrieval. The proposed method collects the texton XOR pattern …