In this paper we propose a novel image representation method that characterizes an image
as a spatiogram--a generalized histogram--of colors quantized by Gaussian Mixture Models …

The proliferation of large number of images has made it necessary to develop systems for
indexing and organizing images for easy access. This has made Content-Based Image …

The tremendous growth in the number of digital images has provoked the need for
improvement in search and retrieval of images from a large database. The biggest challenge …

The content-based image retrieval (CBIR) based on sparse visual features is a challenging
research problem to categorize images into semantically meaningful classes. Different …

Melissopalynology is an important analytical method to identify botanical origin of honey.
Pollen grain recognition is commonly performed by visual inspection by a trained person. An …

This paper presents a new content-based image retrieval (CBIR) method based on image
feature fusion. The deep features are extracted from object-centric and place-centric deep …

Image retrieval is an important research topic in pattern recognition and computer vision. We
propose a novel content-based image retrieval method. At the image description stage, our …

With the development of different image capturing devices, huge amount of complex images
are being produced everyday. Easy access to such images requires proper arrangement …

In this paper, deep convolutional neural network model is developed for classification and
image retrieval purpose. Deep learning techniques obtained deep features from different …

With the rapid development of information technology, the capacity of Web images database
becomes larger and larger. How to quickly and effectively find the desired images in Web …