A novel method for extracting and recognizing logos

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, suffer problems such as, error of logo detection and recognition and slow speed. The proposed method of this study is composed of three sections: In the first section, the exact position of the logo can be identified by the pyramidal tree structure and horizontal and vertical analysis, and in the second section, the logo can be extracted through the algorithm of the boundary extension of feature rectangles. In the third section, after normalizing the size of the logo and eliminating the skew angle, for feature extraction, we first blocked the region encompassing the logo, and then we extract a particular feature by the parameter of the center of gravity of connected component each block. Finally, we use the KNN classification for the recognition of the logo.DOI:http://dx.doi.org/10.11591/ijece.v2i5.129

Graphics Recognition -- from Re-engineering to Retrieval

Invited talk. Colloque avec actes et comité de lecture. internationale.International audienceIn this paper, we discuss how the focus in document analysis, generally speaking, and in graphics recognition more specifically, has moved from re-engineering problems to indexing and information retrieval. After a review of ongoing work on these topics, we propose some challenges for the years to come

Examining Factors of Sports Brand Logo Design that Influence Purchase Intentions : Undergraduate Students Perspective

Logo is vital for a company as it plays the huge role for the growth of business. Every company owner needs and desires their organization to be recognisable and boost the profit of company well. To achieve an impressive success in this competitive and challenging market, they must be one step ahead of their competitors. Thus, a company's meaningful logo can have a major effect on the market and attract new customers to boost revenue. As logo is the essentially branding tool, it is a company's or business's first point of communication and exposure with the world. This research study demonstrates the Signalling Theory which indicates the relationship between colour combination, shapes, lines and fonts used in logo towards purchase intention in sport’s brand product from University Malaysia Sarawak (Unimas) undergraduate students’ perspective. 374 questionnaires were distributed to respondents which are undergraduate students from Unimas for the purpose of testing and analysis of the hypotheses in this research study. The data collected was evaluated with the Statistical Package for the Social Sciences (SPSS) version 26.0. In this research, it was found that the shape of the logo and the line used in the logo had a major positive relationship with purchase intention towards sport brand product from Unimas undergraduate students’ perspective, while the colour combination of the logo and the font used in the logo had a minimal impact on purchase intention towards sport brand product among Unimas undergraduate students. In contrast, the relatively insignificant impact of colour combination and font used in logo on sport brand product implementation tended to be influenced by other variables that yet to be determined

Symbol Recognition: Current Advances and Perspectives

Abstract. The recognition of symbols in graphic documents is an intensive research activity in the community of pattern recognition and document analysis. A key issue in the interpretation of maps, engineering drawings, diagrams, etc. is the recognition of domain dependent symbols according to a symbol database. In this work we first review the most outstanding symbol recognition methods from two different points of view: application domains and pattern recognition methods. In the second part of the paper, open and unaddressed problems involved in symbol recognition are described, analyzing their current state of art and discussing future research challenges. Thus, issues such as symbol representation, matching, segmentation, learning, scalability of recognition methods and performance evaluation are addressed in this work. Finally, we discuss the perspectives of symbol recognition concerning to new paradigms such as user interfaces in handheld computers or document database and WWW indexing by graphical content

SEARCHING HETEROGENEOUS DOCUMENT IMAGE COLLECTIONS

A decrease in data storage costs and widespread use of scanning devices has led to massive quantities of scanned digital documents in corporations, organizations, and governments around the world. Automatically processing these large heterogeneous collections can be difficult due to considerable variation in resolution, quality, font, layout, noise, and content. In order to make this data available to a wide audience, methods for efficient retrieval and analysis from large collections of document images remain an open and important area of research. In this proposal, we present research in three areas that augment the current state of the art in the retrieval and analysis of large heterogeneous document image collections. First, we explore an efficient approach to document image retrieval, which allows users to perform retrieval against large image collections in a query-by-example manner. Our approach is compared to text retrieval of OCR on a collection of 7 million document images collected from lawsuits against tobacco companies. Next, we present research in document verification and change detection, where one may want to quickly determine if two document images contain any differences (document verification) and if so, to determine precisely what and where changes have occurred (change detection). A motivating example is legal contracts, where scanned images are often e-mailed back and forth and small changes can have severe ramifications. Finally, approaches useful for exploiting the biometric properties of handwriting in order to perform writer identification and retrieval in document images are examined

Chart recognition and interpretation in document images

Ph.DDOCTOR OF PHILOSOPH