A new seal verification for Chinese color seal

Automatic seal imprint identification system is highly demanded in oriental countries. Even though several seal identification techniques have been proposed, it is seldom to find the papers on the recovery of lost seal imprint strokes caused by superimposition. In this paper, a new seal verification for Chinese color seal is proposed. This approach segments the seal imprint from the input image in terms of the adaptive thresholds. The lost seal imprint strokes are recovered based on the text stroke width that can be detected automatically. In addition, the moment-based seal verification is to compare the reference seal imprint and the recovered one. Experimental results show that the proposed method is able to correctly and efficiently verify the genuine and forgery seal imprint

Spotted Seals, Phoca largha, in Alaska

The worldwide literature on management of spotted seals, Phoca largha, was reviewed and updated, and aerial surveys weref lown in 1992 and 1993 to determine the species' distribution and abundance in U.S. waters. In April, spotted seals were found only in the Bering Sea ice front. In June, they were seen along deteriorating ice floes and fast ice in Norton Sound. Surveys along most of Alaska's western coast in August and September found over 2,500 spotted seals in Kuskokwim Bay and concentrations of 100-400 seals around Nunivak Island, Scammon Bay, Golovnin Bay/Norton Sound, Cape Espenberg/Kotzebue Sound, and Kasegaluk Lagoon. All of these sites have been used by spotted seals in the past. The sum of the highest counts, irrespective of year, was 3,570 seals (CV =0.06). This is not an abundance estimate for all spotted seals in the Bering Sea, because it does not account for animals in the water, and we did not survey the Asian coast and some islands. Also, spotted seals and harbor seals, Phoca vitulina, are too similar in appearance to be identified accurately from the air, so our results probably include a mix of these species where their ranges overlap

Describing and Understanding Neighborhood Characteristics through Online Social Media

Geotagged data can be used to describe regions in the world and discover local themes. However, not all data produced within a region is necessarily specifically descriptive of that area. To surface the content that is characteristic for a region, we present the geographical hierarchy model (GHM), a probabilistic model based on the assumption that data observed in a region is a random mixture of content that pertains to different levels of a hierarchy. We apply the GHM to a dataset of 8 million Flickr photos in order to discriminate between content (i.e., tags) that specifically characterizes a region (e.g., neighborhood) and content that characterizes surrounding areas or more general themes. Knowledge of the discriminative and non-discriminative terms used throughout the hierarchy enables us to quantify the uniqueness of a given region and to compare similar but distant regions. Our evaluation demonstrates that our model improves upon traditional Naive Bayes classification by 47% and hierarchical TF-IDF by 27%. We further highlight the differences and commonalities with human reasoning about what is locally characteristic for a neighborhood, distilled from ten interviews and a survey that covered themes such as time, events, and prior regional knowledgeComment: Accepted in WWW 2015, 2015, Florence, Ital

Research on Event Extraction Model Based on Semantic Features of Chinese Words

Event Extraction (EE) is an important task in Natural Language Understanding (NLU). As the complexity of Chinese structure, Chinese EE is more difficult than English EE. According to the characteristics of Chinese, this paper designed a Semantic-GRU (Sem-GRU) model, which integrates Chinese word context semantics, Chinese word glyph semantics and Chinese word structure semantics. And this paper uses the model for Chinese Event Trigger Extraction (ETE) task. The experiment is compared in two tasks: ETE and Named Entity Recognition (NER). In ETE, the paper uses ACE 2005 Chinese event dataset to compare the existing research, the effect reaches 75.8 %. In NER, the paper uses MSRA dataset, which reaches 90.3 %, better than other models

Non-english and non-latin signature verification systems: A survey

Signatures continue to be an important biometric because they remain widely used as a means of personal verification and therefore an automatic verification system is needed. Manual signature-based authentication of a large number of documents is a difficult and time consuming task. Consequently for many years, in the field of protected communication and financial applications, we have observed an explosive growth in biometric personal authentication systems that are closely connected with measurable unique physical characteristics (e.g. hand geometry, iris scan, finger prints or DNA) or behavioural features. Substantial research has been undertaken in the field of signature verification involving English signatures, but to the best of our knowledge, very few works have considered non-English signatures such as Chinese, Japanese, Arabic etc. In order to convey the state-of-the-art in the field to researchers, in this paper we present a survey of non-English and non-Latin signature verification systems

Soundings: the Newsletter of the Monterey Bay Chapter of the American Cetacean Society. 2007

(PDF contains 88 pages.