For many years, various local descriptors that are insensitive to geometric changes such as viewpoint, rotation, and scale changes, have been attracting attention due to their promising performance. However, most existing local descriptors including the SIFT (Scale Invariant Feature Transform) are based on luminance information rather than color information thereby resulting in instability to p...

Convolutional Neural Network (NN) has gained a lot of attention of the researchers due to its high accuracy in classification and feature learning. In this paper, we evaluated the performance of CNN used as feature for image retrieval with the gold standard feature, aka SIFT. Experiments are conducted on famous Oxford 5k data-set. The mAP of SIFT and CNN is 0.6279 and 0.5284, respectively. The ...

Latest results indicate that features learned via convolutional neural networks outperform previous descriptors on classification tasks by a large margin. It has been shown that these networks still work well when they are applied to datasets or recognition tasks different from those they were trained on. However, descriptors like SIFT are not only used in recognition but also for many correspo...

car license plate recognition is addressed in this paper. given the development of intelligent transportation systems, it is absolutely essential to implement a strong license plate recognition system. efforts were made to put forward a novel reliable method for car license plate recognition in iran. each license plate recognition system comprises three main parts. the first part is the license...

Zhai and Shah (2006) proposed a model of spatiotemporal saliency using a combination of temporal and spatial attention models. The temporal model utilized Lowe’s SIFT (2004) to compute feature points and the correspondences between them in successive frames. Bay, Tuytelaars, & Van Gool introduced SURF (2006) as an alternative feature detector and descriptor. The authors of SURF show that it is ...

Abstract. While image registration has been studied in different areas of computer vision, aligning images depicting different scenes remains a challenging problem, closer to recognition than to image matching. Analogous to optical flow, where an image is aligned to its temporally adjacent frame, we propose SIFT flow, a method to align an image to its neighbors in a large image collection consi...

Copy-Move is one of the most common technique for digital image tampering or forgery. Copy-Move in an image might be done to duplicate something or to hide an undesirable region. In some cases where these images are used for important purposes such as evidence in court of law, it is important to verify their authenticity. In this paper the authors propose a novel method to detect single region ...

This paper investigates the effectiveness of image description using detectors and keypoint descriptors for similarity evaluation. SIFT, SURF, ORB, BRISK methods are compared detection matching procedures. Similarity coefficients computed each pair, corresponding coefficient matrices constructed analysis. An evaluation speed was conducted. It found that SIFT yielded he SURF method performed bet...

The nuclear receptor (NR) superfamily represents an important group of regulating factors that control the expression of a number of target genes including those encoding important drug metabolizing enzymes and drug transporters. Single nucleotide polymorphism (SNP) is the most common mutation in the human genome and a large number of SNPs have been identified to date. It is unlikely to examine...

Feature extraction is a widely used technique in the field of image recognition, multimedia information retrieval. known techniques for this feature extractions are ORB, SIFT, SURF, Wavelets and many more. One part of MIR is object recognition, and with object recognition comes object finding, or homograph finding. This uses a method called RANSAC to determine where an object is in a scene, usi...