People are regularly bombarded with logos in an attempt to improve brand recognition, and logos are often designed with the central purpose of memorability. The ubiquitous Apple logo is a simple design and is often referred to as one of the most recognizable logos in the world. The present study examined recall and recognition for this simple and pervasive logo and to what degree metamemory (co...

In this paper we propose a method for logo recognition using deep learning. Our recognition pipeline is composed of a logo region proposal followed by a Convolutional Neural Network (CNN) specifically trained for logo classification, even if they are not precisely localized. Experiments are carried out on the FlickrLogos-32 database, and we evaluate the effect on recognition performance of synt...

Real-world logo recognition is challenging mainly due to various viewpoints and different lighting conditions. Currently, the most popular approaches are usually based on bag-of-words model due to their good performance. However, their shortcomings lie in two main aspects: (1) wrong recognition results caused by mismatching of keypoints. (2) high computational complexity and extra noise caused ...

Problem statement: The shape-based logo recognition systems have been developed to automate the logo registration process. The logo recognition operation faces many challenges such as having to recognize logos that might be scaled, rotated, translated and added with noises. Different types of logo’s shapes further add to the complex nature of this problem. Approach: We developed a logo recognit...

Abstract Vehicle Logo Detection (VLD) is of great significance to Intelligent Transportation Systems (ITS). Although many methods have been proposed for VLD, it remains a challenging problem. To improve the VLD accuracy, an Intersection over Average (IoAverage) loss enhancing bounding box regression. The IoAverage accelerates convergence regression than using Union (IoU) loss. In experiments, h...

This paper discusses the implementation of imrestaurant(), a MATLAB function for feature-based restaurant logo recognition. The algorithm works by first applying SIFT to a logo database and then creating a hierarchical vocabulary tree using K-means clustering. The input to the algorithm is a photograph of an image logo, which is first filtered to reduce noise. Then SIFT is applied to the input ...

Received Jul 12, 2012 Revised Aug 30, 2012 Accepted Sep 9, 2012 Nowadays, the high volume of archival documents has made it exigent to store documents in electronic databases. A text logo represents the ownership of the text, and different texts can be categorized by it; for this reason, different methods have been presented for extracting and recognizing logos. The methods presented earlier, s...

Logo detection in images and videos is considered a key task for various applications, such as vehicle logo traffic-monitoring systems, copyright infringement detection, contextual content placement. The main contribution of this work the application emerging deep learning techniques to perform brand recognition tasks through use multiple modern convolutional neural network models. In work, pre...

The problem of logo recognition is of great interest in the document domain, especially for databases, because of its potential for identifying the source of the document and its generality as a recognition problem. By recognizing the logo we obtain semantic information about the document, which may be useful in deciding whether or not to analyze the textual components. In this paper, we presen...