Closing the semantic gap in medical image analysis is critical. Access to large-scale
datasets might help to narrow the gap. However, large and balanced datasets may not …

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 …

In facial expression recognition applications, the classification accuracy decreases because
of the blur, illumination and localization problems in images. Therefore, a robust emotion …

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

This paper proposes a new pattern descriptor called directional local ternary quantized
extrema pattern (DLTerQEP) for biomedical image indexing and retrieval. The standard local …

Feature extraction and its matching are two critical tasks in image retrieval. This paper
presents a new methodology for content-based image retrieval by integrating three features …

In this paper, a new coding scheme, local Gabor maximum edge position octal patterns
(LGMEPOP) is proposed for content based image retrieval. The standard local binary pattern …

Color features and local geometrical structures are the two basic image features which are
sufficient to convey the image semantics. Both of these features show diverse nature on the …

This paper proposes a novel feature descriptor, named local quantized extrema patterns
(LQEP) for content based image retrieval. The standard local quantized patterns (LQP) …

A novel image indexing algorithm for Content Based Image Retrieval (CBIR) using Local
Energy Oriented Patterns (LEOP) is proposed in this paper. LEOP encodes pixel level …