The application of machine learning to radiological images is an increasingly active
research area that is expected to grow in the next five to ten years. Recent advances in …

This paper presents a content-based image retrieval technique that focuses on extraction
and reduction in multiple features. To obtain multi-level decomposition of the image by …

Dental caries detection, in the past, has been a challenging task given the amount of
information got from various radiographic images. Several methods have been introduced to …

A new image retrieval technique using local neighborhood difference pattern (LNDP) has
been proposed for local features. The conventional local binary pattern (LBP) transforms …

In this paper, a new texture descriptor based on the local neighborhood intensity difference
is proposed for content based image retrieval (CBIR). For computation of texture features …

Texture is a prominent feature of image and very useful in feature extraction for image
retrieval application. Statistical and structural patterns have been proposed for image …

Many content-based image retrieval (CBIR) methods are being developed to store more and
more information about images in shorter feature vectors and to improve image retrieval …

In the era of massive data production through the internet and social media, the volume of
images generated is immense. Storing and retrieving relevant images efficiently pose …

Although there has been a growing body of work for face recognition, it is still a challenging
task for faces under occlusion with limited training samples. In this work, we propose a novel …

A rapid growth in medical ultrasound database makes it difficult for medical practitioners to
manage and search relevant data with good efficiency. Hence, a novel image retrieval …