The complexity of multimedia contents is significantly increasing in the current digital world.
This yields an exigent demand for develo** highly effective retrieval systems to satisfy …

In this paper, we propose a novel benchmark for evaluating local image descriptors. We
demonstrate that the existing datasets and evaluation protocols do not specify …

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 …

In these modern days, digital images become prominent information on the Internet and
Social Media. The images can have a number of features with many secrets. To get these …

Detecting text in natural images is an important prerequisite. In this paper, we propose a
novel text detection algorithm, which employs edge-enhanced Maximally Stable Extremal …

SIFT-like local feature descriptors are ubiquitously employed in computer vision applications
such as content-based retrieval, video analysis, copy detection, object recognition, photo …

We introduce a simple modification of local image descriptors, such as SIFT, based on
pooling gradient orientations across different domain sizes, in addition to spatial locations …

Mobile phones have evolved into powerful image and video processing devices equipped
with high-resolution cameras, color displays, and hardware-accelerated graphics. They are …

Binary keypoint descriptors provide an efficient alternative to their floating-point competitors
as they enable faster processing while requiring less memory. In this paper, we propose a …

Rapidly growing applications on smartphones have provided an excellent platform for
mobile visual search. Most of previous visual search systems adopt the framework of” Bag of …