Biometric face reorganization is an established means for the prevention of frauds in financial transactions and security issues. In particular, face verification has been extensively used to endorse financial transac...
详细信息
ISBN:
(纸本)9789811021046;9789811021039
Biometric face reorganization is an established means for the prevention of frauds in financial transactions and security issues. In particular, face verification has been extensively used to endorse financial transactions. Thermal face recognition is an upcoming approach in this field. This work proposes a robust thermal face recognition system based on face localized scale-invariant feature transform (FLSIFT). FLSIFT tackles the problem of thermal face recognition with complex backgrounds. Experimental results of proposed FLSIFT thermal face recognition system are compared with the existing Blood Vessel pattern method. To test the performance of proposed and existing method, a new thermal face database consisting of Indian people and variations in the background is developed. The thermal facial images of 113 subjects are captured for this purpose. The test results show that the recognition accuracy of Blood Vessel pattern technique and FLSIFT on face images with simple background is 79.28 % and 100 %, respectively. Moreover, the test performance on the complex background for the two methods is found to be 5.55 % and 98.14 %, respectively. It may be noted that FLSIFT is capable to handle background changes more efficiently and the performance is found to be robust.
作者:
Hao, PuZhai, Jun-HaiZhang, Su-FangHebei Univ
Coll Math & Informat Sci Key Lab Machine Learning & Computat Intelligence Baoding 071002 Hebei Peoples R China Zhejiang Normal Univ
Coll Math Phys & Informat Engn Jinhua 321004 Peoples R China China Meteorol Adm
China Meteorol Adm Training Ctr Hebei Branch Baoding 071000 Peoples R China
As a deep learning model, convolutional neural network (CNN) has greatly attracted attentions from researchers and has found its successful applications in many fields such as computer vision, patternrecognition, nat...
详细信息
ISBN:
(纸本)9781538604083
As a deep learning model, convolutional neural network (CNN) has greatly attracted attentions from researchers and has found its successful applications in many fields such as computer vision, patternrecognition, natural language processing, etc. However, the training of deep convolutional neural networks (DCNN) is very time-consuming and memory intensive. Inspired by the idea of extreme learningmachine (ELM), this paper proposed a simple and effective method for image classification. The proposed method employs a neural network with 6 layers to classify images. The neural network consists of two modules: CNN and ELM network. The CNN has two convolutional layers and two pooling layers (also called subsampling layers). The ELM network is a single-hidden layer feed-forward neural network (SLFN). As does in ELM, the parameters of convolutional kernels of CNN are also randomly assigned. Our experimental results show that although this method is simple, it is very effective.
Bangla is one of the most popular script from eastern part of India with a demographic distribution of 212 million of population, used in languages like Bengali, Assamese, Manipuri etc. There are several works reporte...
详细信息
ISBN:
(纸本)9789811048593;9789811048586
Bangla is one of the most popular script from eastern part of India with a demographic distribution of 212 million of population, used in languages like Bengali, Assamese, Manipuri etc. There are several works reported in literature considering Bangla script in the areas of Bangla OCR, postal automation, writer verification, online document analysis, script identification etc. They need more attention from the researchers as almost all of the mentioned topics are yet far from getting maturity. In this paper, a study on the advancement of those techniques with emphasis on Bangla script is presented. Also, some future directions in this field will be discussed.
Thinning of fingerprint ridges plays a vital role in fingerprint identification systems as it simplifies the subsequent processingsteps like fingerprint classification and feature extraction. In this paper, we analyz...
详细信息
ISBN:
(纸本)9789811048593;9789811048586
Thinning of fingerprint ridges plays a vital role in fingerprint identification systems as it simplifies the subsequent processingsteps like fingerprint classification and feature extraction. In this paper, we analyze some of the parallel thinning algorithms and have proposed a methodology for skeletonization of fingerprint ridges directly on gray scale images as significant amount of information and features are lost during the binarization process. This algorithm is based on conditionally eroding the gray level ridges iteratively until a one pixel thick ridge is obtained. Refinement procedures have also been proposed to improve the quality of ridge skeleton. Experiments conducted on sample fingerprint images collected using an optical fingerprint Reader exhibit desirable features of the proposed approach.
This paper presents a new method of liquid surface location based on visual analysis, which was proposed with the visual navigation of imagery processing technology. Firstly, hospital medical infusion bottle image was...
详细信息
ISBN:
(纸本)9781538608432
This paper presents a new method of liquid surface location based on visual analysis, which was proposed with the visual navigation of imagery processing technology. Firstly, hospital medical infusion bottle image was binarized by the statistical methods of energy. Secondly, binary image was carried on the image segmentation through the projection statistics method and the Shen algorithm. Finally, horizontal projection image is smoothed by Shen algorithm. The experimental results show that the proposed method can accurately locate and real-time tracking of medical infusion bottle surface.
Ultrasound (US) imaging plays an important role in medical imaging technologies. It is widely used because of its ease of use and low cost compared to other imaging techniques. Specifically, ultrasound imaging is used...
详细信息
ISBN:
(纸本)9781450352437
Ultrasound (US) imaging plays an important role in medical imaging technologies. It is widely used because of its ease of use and low cost compared to other imaging techniques. Specifically, ultrasound imaging is used in the detection of the Achilles Tendon (AT) pathologies as it detects important details. For example, US imaging is used for AT rupture that affects about 1 in 5,000 people worldwide. Decision support systems are important in medical imaging, as they assist radiologist in detecting probable diagnoses and lesions. The work presented in this paper concerns the development of a software application to detect changes in the AT ultrasound images and subsequently classify them into normal or abnormal. We propose an approach that fully automates the detection for the Region of Interest (ROI) in ultrasound AT images. The original image is divided into six blocks with 1 cm size in each direction. The blocks lie inside the vulnerable area considered as our ROI. The proposed system achieved an accuracy of 97.21%.
We present a technique that uses edge map to separate panels from stitched compound figures appearing in biomedical scientific research articles. Since such figures may comprise images from different imaging modalitie...
详细信息
ISBN:
(纸本)9789811048593;9789811048586
We present a technique that uses edge map to separate panels from stitched compound figures appearing in biomedical scientific research articles. Since such figures may comprise images from different imaging modalities, separating them is a critical firststep for effective biomedical content-based image retrieval (CBIR). We study state-of-the-art edge detection algorithms to detect gray-level pixel changes. It then applies a line vectorization process that connects prominent broken lines along the panel boundaries while eliminating insignificant line segments within the panels. We have validated our fully automatic technique on a subset of stitched multipanel biomedical figures extracted from articles within the Open Access subset of PubMed Central repository, and have achieved precision and recall of 74.20% and 71.86%, respectively, in less than 0.272 s per image, on average.
In the paradigm of smart cities, video surveillance is becoming a widely-applied technology to help improve the quality of human life in the era of digital living, where pedestrian detection is one of the key componen...
详细信息
ISBN:
(纸本)9781450352437
In the paradigm of smart cities, video surveillance is becoming a widely-applied technology to help improve the quality of human life in the era of digital living, where pedestrian detection is one of the key components for people-centered smart cities applications including wellbeing, security, traffic guiding, and unmanned vehicles, etc. While so far most surveillance cameras are of low quality resolution for cost-saving reasons, the impact of the image resolution on detection accuracy becomes a concerned issue. Though lower resolution can save the cost as well as the processing time, it has not been clearly reported how the resolution can impact on the detection accuracy. In this paper, we investigate the limit of low resolution cameras with regards to the accuracy of the pedestrian detection, and experimentally demonstrate its impact on the most widely-applied HOG-SVM pedestrian detector, which is a combination of Histogram of Oriented Gradient (HOG) and Support Vector machine (SVM) for pedestrian detection. From our experiments, it is found that there is an optimal resolution to balance between speed and accuracy, while we show in our experiments that the resolution has apparent influence on both the accuracy and the computing time.
The proceedings contain 21 papers. The topics discussed include: automated image quality assessment for certificates and bills;predicting application failure in cloud: a machinelearning approach;an automation method ...
ISBN:
(纸本)9781538620083
The proceedings contain 21 papers. The topics discussed include: automated image quality assessment for certificates and bills;predicting application failure in cloud: a machinelearning approach;an automation method of SLA contract of web APIs and its platform based on blockchain concept;social network types: an emergency social network approach - a concept of possible inclusion of emergency posts in social networks through an API;crowdsourcing workflow optimization to internal worker crowds;cost-effective social network data placement and replication using graph-partitioning;a method for dealing with data sparsity and cold-start limitations in service recommendation using personalized preferences;and service pattern evaluation: studying profitability from perspective of resource.
The proceedings contain 9 papers. The topics discussed include: automatic detection of stance towards vaccination in online discussion forums;analyzing the causes of depressed mood from depression vulnerable individua...
ISBN:
(纸本)9781948087070
The proceedings contain 9 papers. The topics discussed include: automatic detection of stance towards vaccination in online discussion forums;analyzing the causes of depressed mood from depression vulnerable individuals;multivariate linear regression of symptoms-related tweets for infectious gastroenteritis scale estimation;incorporating dependency trees improve identification of pregnant women on social media platforms;using a recurrent neural network model for classification of tweets conveyed influenza-related information;ZikaHack 2016: a digital disease detection competition;a method to generate a machine-labeled data for biomedical named entity recognition with various sub-domains;enhancing drug-drug interaction classification with corpus-level feature and classifier ensemble;and chemical-induced disease detection using invariance-based patternlearning model.
暂无评论