State-of-the-Art: A Systematic Literature Review on Image Segmentation in Latent Fingerprint Forensics

2019 ◽  
Vol 12 ◽  
Author(s):  
Megha Chhabra ◽  
Manoj Kumar Shukla ◽  
Kiran Kumar Ravulakollu
Keyword(s):  
Image Segmentation ◽  
Background Noise ◽  
State Of The Art ◽  
Recognition Rate ◽  
Poor Quality ◽  
Latent Fingerprint ◽  
In The Beginning ◽  
The Comparative Study ◽  
Finger Skin

: Latent fingerprints are unintentional finger skin impressions left as ridge patterns at crime scenes. A major challenge in latent fingerprint forensics is the poor quality of the lifted image from the crime scene. Forensics investigators are in permanent search of novel outbreaks of the effective technologies to capture and process low quality image. The accuracy of the results depends upon the quality of the image captured in the beginning, metrics used to assess the quality and thereafter level of enhancement required. The low quality of the image collected by low quality scanners, unstructured background noise, poor ridge quality, overlapping structured noise result in detection of false minutiae and hence reduce the recognition rate. Traditionally, Image segmentation and enhancement is partially done manually using help of highly skilled experts. Using automated systems for this work, differently challenging quality of images can be investigated faster. This survey amplifies the comparative study of various segmentation techniques available for latent fingerprint forensics.

scholarly journals A Multiscale CNN-CRF Framework for Environmental Microorganism Image Segmentation

2020 ◽  
Vol 2020 ◽  
pp. 1-27
Author(s):  
Jinghua Zhang ◽  
Chen Li ◽  
Frank Kulwa ◽  
Xin Zhao ◽  
Changhao Sun ◽  
...  
Keyword(s):  
Image Segmentation ◽  
State Of The Art ◽  
Conditional Random Field ◽  
Segmentation Method ◽  
Recall Accuracy ◽  
Evaluation Indexes ◽  
Segmentation Quality ◽  
Segmentation Approach ◽  
Overall Evaluation

To assist researchers to identify Environmental Microorganisms (EMs) effectively, a Multiscale CNN-CRF (MSCC) framework for the EM image segmentation is proposed in this paper. There are two parts in this framework: The first is a novel pixel-level segmentation approach, using a newly introduced Convolutional Neural Network (CNN), namely, “mU-Net-B3”, with a dense Conditional Random Field (CRF) postprocessing. The second is a VGG-16 based patch-level segmentation method with a novel “buffer” strategy, which further improves the segmentation quality of the details of the EMs. In the experiment, compared with the state-of-the-art methods on 420 EM images, the proposed MSCC method reduces the memory requirement from 355 MB to 103 MB, improves the overall evaluation indexes (Dice, Jaccard, Recall, Accuracy) from 85.24%, 77.42%, 82.27%, and 96.76% to 87.13%, 79.74%, 87.12%, and 96.91%, respectively, and reduces the volume overlap error from 22.58% to 20.26%. Therefore, the MSCC method shows great potential in the EM segmentation field.

Fast and Robust Personal Identification by Fusion of Finger Vein and Finger-Knuckle-Print Images

2014 ◽  
Vol 556-562 ◽  
pp. 5085-5088 ◽  
Author(s):  
Wen Ming Yang ◽  
Yi Chao Li ◽  
Qing Min Liao
Keyword(s):  
State Of The Art ◽  
Recognition Rate ◽  
Test Sample ◽  
Personal Identification ◽  
Identification Methods ◽  
Person Recognition ◽  
Finger Vein ◽  
Coarse To Fine ◽  
Selection Of

Finger vein and finger-knuckle-print have been studied for personal identification. Methods utilizing direction and location of finger veins have achieved promising performance. However, it is sensitive to quality of finger vein images and it is slow. In this paper, we develop a fast and robust algorithm for person recognition using a coarse-to-fine classifier. 2DPCA is used for coarse selection of k nearest candidates. To increase the robustness of the algorithm, a candidate person is selected when either its finger vein or finger-knuckle-print is near the corresponding test sample. Competitive coding schema is then conducted on the n (n <= 2k) candidates and test images for final classification. Experimental results show that our method is faster and achieved comparable recognition rate with state-of-the-art methods.

scholarly journals SentiGAN: Generating Sentimental Texts via Mixture Adversarial Networks

2018 ◽  
Author(s):  
Ke Wang ◽  
Xiaojun Wan
Keyword(s):  
Natural Language ◽  
State Of The Art ◽  
Natural Language Generation ◽  
Poor Quality ◽  
Experimental Results ◽  
Text Generation ◽  
Language Generation ◽  
Adversarial Networks

Generating texts of different sentiment labels is getting more and more attention in the area of natural language generation. Recently, Generative Adversarial Net (GAN) has shown promising results in text generation. However, the texts generated by GAN usually suffer from the problems of poor quality, lack of diversity and mode collapse. In this paper, we propose a novel framework - SentiGAN, which has multiple generators and one multi-class discriminator, to address the above problems. In our framework, multiple generators are trained simultaneously, aiming at generating texts of different sentiment labels without supervision. We propose a penalty based objective in the generators to force each of them to generate diversified examples of a specific sentiment label. Moreover, the use of multiple generators and one multi-class discriminator can make each generator focus on generating its own examples of a specific sentiment label accurately. Experimental results on four datasets demonstrate that our model consistently outperforms several state-of-the-art text generation methods in the sentiment accuracy and quality of generated texts.

scholarly journals Biomarkers in Inflammatory Bowel Disease-Associated Spondyloarthritis: State of the Art and Unmet Needs

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Devis Benfaremo ◽  
Michele Maria Luchetti ◽  
Armando Gabrielli
Keyword(s):  
Inflammatory Bowel Disease ◽  
Bowel Disease ◽  
State Of The Art ◽  
Systemic Disease ◽  
Diagnostic Delay ◽  
Joint Damage ◽  
Poor Quality ◽  
Inflammatory Bowel ◽  
Biomarker Research

Inflammatory bowel disease-associated spondyloarthritis is a systemic disease characterized by the chronic inflammation of both the gastrointestinal tract and the musculoskeletal system. Since inflammatory bowel disease-associated spondyloarthritis has been associated with a significant diagnostic delay, which may lead to poor quality of life and progression of joint damage, efforts to discover new reliable and noninvasive diagnostic biomarkers have been made. We reviewed the state of the art of biomarker research in inflammatory bowel disease-associated spondyloarthritis, showing that to date it has been largely unsatisfactory. Only a few of the biomarkers that have been investigated are likely to enter the clinical practice upon further validation in independent cohorts. The research of new and innovative biomarkers for inflammatory bowel disease-associated spondyloarthritis is warranted.

A Review of Fingerprint Image Pre-processing

2014 ◽  
Vol 69 (2) ◽  
Author(s):  
Alaa Ahmed Abbood ◽  
Ghazali Sulong ◽  
Sabine U. Peters
Keyword(s):  
Feature Extraction ◽  
State Of The Art ◽  
Noise Removal ◽  
Extraction Methods ◽  
Poor Quality ◽  
The Other ◽  
Gray Level ◽  
Fingerprint Image ◽  
False Acceptance

Fingerprints are the most widely used form of human identification and verification due to their uniqueness and permanence. For that reason, many Automatic Fingerprint Identification Systems (AFIS) have been commercially produced and accepted by the international community. Though their performance is good, there is still room for improvement. One of the main concerns is poor fingerprint images that are caused by capturing devices. Thus, to improve the efficiency of AFIS, both image enhancement and feature extraction methods are required to be implemented. An effective feature extraction depends on the quality of its image whereby high image quality would normally produce genuine features. On the other hand, poor quality would lead to fake features that will result in false acceptance. This paper reviews several state-of-the-art methods of fingerprint image pre-processing including gray level normalization, noise removal and segmentation.

Innovative Outlier Removal Techniques to Enhance Signature Authentication Accuracy for Smart Society

2019 ◽  
Vol 10 (2) ◽  
pp. 64-83
Author(s):  
Anindita Desarkar ◽  
Shisna Sanyal ◽  
Anupam Baidya ◽  
Ajanta Das ◽  
Chitrita Chaudhuri
Keyword(s):  
Performance Evaluation ◽  
Recognition Rate ◽  
Poor Quality ◽  
Machine Learning Algorithms ◽  
True Positive ◽  
Outlier Removal ◽  
True Negative ◽  
Subsequent Performance ◽  
The Poor

A smart society is an empowered society, which can improve the lives of its citizens by using the latest innovations and technologies. This improvement can happen in several dimensions out of which security is a major one. Inconsistency and forgery are very common phenomenon where handwritten signatures are often preserved for training a classifier to authenticate a person. The removal of outliers, at the outset, obviously improves the quality of training and the classifier. The present article deals with the mechanized segregation of the poor-quality authentic signatures from reliable ones. Machine learning algorithms for outlier handling utilizing clustering, classification and statistical techniques have been implemented in this context. Subsequent performance evaluation after outlier removal reflects improvement of both true positive and true negative recognition rate accuracy. The performance evaluation presents the significant differences between authentication accuracy and forgery accuracy in the context of building a safe, secure and smart society.

scholarly journals EANet: Edge-Aware Network for the Extraction of Buildings from Aerial Images

2020 ◽  
Vol 12 (13) ◽  
pp. 2161 ◽  
Author(s):  
Guang Yang ◽  
Qian Zhang ◽  
Guixu Zhang
Keyword(s):  
Remote Sensing ◽  
Image Segmentation ◽  
Data Augmentation ◽  
State Of The Art ◽  
Receptive Fields ◽  
Aerial Images ◽  
Remote Sensing Images ◽  
Global Features ◽  
Multi Scale

Deep learning methods have been used to extract buildings from remote sensing images and have achieved state-of-the-art performance. Most previous work has emphasized the multi-scale fusion of features or the enhancement of more receptive fields to achieve global features rather than focusing on low-level details such as the edges. In this work, we propose a novel end-to-end edge-aware network, the EANet, and an edge-aware loss for getting accurate buildings from aerial images. Specifically, the architecture is composed of image segmentation networks and edge perception networks that, respectively, take charge of building prediction and edge investigation. The International Society for Photogrammetry and Remote Sensing (ISPRS) Potsdam segmentation benchmark and the Wuhan University (WHU) building benchmark were used to evaluate our approach, which, respectively, was found to achieve 90.19% and 93.33% intersection-over-union and top performance without using additional datasets, data augmentation, and post-processing. The EANet is effective in extracting buildings from aerial images, which shows that the quality of image segmentation can be improved by focusing on edge details.

An experience of performing spirometry by trained general practitioners

2020 ◽  
pp. 34-36
Author(s):  
M. A. Pokhaznikova ◽  
E. A. Andreeva ◽  
O. Yu. Kuznetsova
Keyword(s):  
General Practitioners ◽  
Quality Criteria ◽  
Poor Quality ◽  
Male Gender ◽  
Study Research ◽  
The Poor ◽  
Quality Of Research ◽  
Forced Expiratory Maneuver ◽  
Maximal Effort

The article discusses the experience of teaching and conducting spirometry of general practitioners as part of the RESPECT study (RESearch on the PrEvalence and the diagnosis of COPD and its Tobacco-related aetiology). A total of 33 trained in spirometry general practitioners performed a study of 3119 patients. Quality criteria met 84.1% of spirometric studies. The analysis of the most common mistakes made by doctors during the forced expiratory maneuver is included. The most frequent errors were expiration exhalation of less than 6s (54%), non-maximal effort throughout the test and lack of reproducibility (11.3%). Independent predictors of poor spirogram quality were male gender, obstruction (FEV1 /FVC<0.7), and the center where the study was performed. The number of good-quality spirograms ranged from 96.1% (95% CI 83.2–110.4) to 59.8% (95% CI 49.6–71.4) depending on the center. Subsequently, an analysis of the reasons behind the poor quality of research in individual centers was conducted and the identified shortcomings were eliminated. The poor quality of the spirograms was associated either with the errors of the doctors who undertook the study or with the technical malfunctions of the spirometer.

The first experience of bipolar transurethral operations in surgery of benign prostatic hyperplasia

2018 ◽  
pp. 10-20
Author(s):  
Н.А. Глотов ◽  
Н.Е. Соколов ◽  
Ю.Б. Смоляков
Keyword(s):  
Benign Prostatic Hyperplasia ◽  
Prostatic Hyperplasia ◽  
Medium Term ◽  
Significance Level ◽  
The Road ◽  
Surgical Methods ◽  
The Comparative Study ◽  
Endoscopic Methods ◽  
Qualitative Characteristics

Представлены результаты внедрения в хирургическую практику урологического отделения Дорожной клинической больницы г. Ярославль биполярной техники трансуретральной резекции (БТУР) и энуклеации простаты (ТУЭБ) для лечения доброкачественной гиперплазии предстательной железы (ДГПЖ) средних и больших размеров. В сравнительное исследование включено 164 пациента, разделенных по методам операции на 2 основные группы (ТУЭБ - 33 человека, БТУР - 49) и 2 контрольные (открытая простатэктомия - ОПЭ - 38 и монополярная ТУР - 44). Для новых эндоскопических методов установлено значимое снижение объема кровопотери, частоты геморрагических осложнений, сроков послеоперационной катетеризации и госпитализации. Для количественной оценки различий средних и относительных показателей использо-вали непараметрический критерий Манна-Уитни, оценка качественных признаков проводилась с применением критерия Пирсона (χ2), уровень значимости различий для исследования выбран р ≤ 0,05. Анализ послеоперационной динамики клинических показателей в среднесрочной перспективе показал сходную радикальность и эффектив-ность сравниваемых методов. Установленные меньшая инвазивность, большая безопасность и лучшая переносимость биполярных эндоскопических операций демонстрируют перспективность их внедрения взамен бывших стандартных хирургических методов, что позволит повысить качество оперативного лечения и сократить затраты стационара. The results of the introduction into surgical practice of the urological Department of the road clinical hospital of Yaroslavl bipolar technique of transurethral resection (BTTR) and enucleation of the prostate (EOTP) for the treatment of benign prostatic hyperplasia (BPH) of medium and large sizes are presented. The comparative study included 164 patients, divided by the methods of surgery into 2 main groups (EOTP - 33 people, BTTR - 49) and 2 control (open prostatectomy - OPE - 38 and monopolar TTR - 44). For new endoscopic methods, a significant reduction in the volume of blood loss, the frequency of hemorrhagic complications, the timing of postoperative catheterization and hospitalization was established. Nonparametric Mann-Whitney test was used to quantify the differences in mean and relative indicators, qualitative characteristics were evaluated using Pearson test (χ2), the significance level of the differences for the study was chosen p ≤ 0.05. Analysis of postoperative dynamics of clinical parameters in the medium term showed similar radicality and effectiveness of the compared methods. The lower invasiveness, greater safety and better tolerability of bipolar endoscopic operations demonstrate the prospects of their implementation instead of the former standard surgical methods, which will improve the quality of surgical treatment and reduce the costs of the hospital.

KUALITAS HIDUP PASIEN STROKE DI POLIKLINIK RAWAT JALAN RUMAH SAKIT SWASTA YOGYAKARTA

2019 ◽  
Vol 7 (3) ◽  
pp. 232-237
Author(s):  
Hana Larasati ◽  
Theresia Titin Marlina
Keyword(s):  
Quality Of Life ◽  
Social Relations ◽  
Hemorrhagic Stroke ◽  
Poor Quality ◽  
Social Dimension ◽  
Stroke Patients ◽  
Sampling System ◽  
Post Stroke ◽  
Psychological Dimension

Background: stroke is a disorder of nervous system function that occurs suddenly and is caused by brain bleeding disorders that can affect the quality of life physical dimensions, social dimensions, psychological dimensions, environmental dimensions. Based on the result of Lumbu study (2015) the number of samples were 71 people collected data using the (WHOQOL-BREF). There were 56 people (78,9%) had the poor quality of life of post stroke. The mean of post-stroke quality of life domain was physical domain (45,27%), psychological domain (49,87%), social relations domain (48,15%) and environmental domain (50.01%). Objective: the purpose of the study was know the quality of life of the stroke patients in Outpatient Polyclinic of Private Hospital in Yogyakarta. Methods: used descriptive quantitative by using questionnaire test of purposive sampling system based on patients who have been affected of ischemic or hemorrhagic stroke before, number 30 respondents. Result: quality of life of stroke patient of medium physical dimension (67%), psychological dimension (71%), social dimension (67%), dimension good environment (63%). Conclusion: the quality of life of stroke patients of physical dimension, psychological dimension, and moderate social dimension, while the quality of life of stroke patients were good environmental dimension.   Keywords: Hemorrhagic stroke, ischemic stroke, quality of life

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