19 research outputs found
Review of Sequential Access Method for Fingerprint Identification
Real time fingerprint identification is usually equipped with specific computation machine architecture to optimize speed factor. Focusing on achieving better speed performance of fingerprint identification on common computation machine, a disquisition was conducted on sequential access method for fingerprint identification, with its underlying data structure designed to work with parallel processing. Hypothetically, parallel processing based on multi-cores processor technology, can give faster result without reducing accuracy. If multi core processor was detected, simultaneous processes would run on fingerprint matching-pairs to find its similarity score, respectively. Experiment confirms that speed performance of fingerprint identification using sequential access method with parallel processing outperforms the one without parallel processing. For both strategy, even though using parallel processing confirms faster result, experiment shows that searching time O(n) still linearly depends on number of fingerprints in database. Avoiding such searching time trend, hypothetically, need strategy of direct access method utilization
Fingerprint Direct-Access Strategy Using Local-Star-Structure-based Discriminator Features: A Comparison Study
This paper describes a comparison study of the proposed fingerprint direct-access strategy using local-star-topology-based discriminator features, including internal comparison among different concerned configurations, and external comparison to the other strategies. Through careful minutiae-based feature extraction, hashing-based indexing-retrieval mechanism, variable-threshold-on-score-ratio-based candidate-list reduction technique, and hill-climbing learning process, this strategy was considered promising, as confirmed by the experiment results. For particular aspect of external accuracy comparison, this strategy outperformed the others over three public data sets, i.e. up to Penetration Rate (PR) 5%, it consistently gave lower Error Rate (ER). By taking sample at PR 5%, this strategy produced ER 4%, 10%, and 1% on FVC2000 DB2A, FVC2000 DB3A, and FVC2002 DB1A, respectively. Another perspective if accuracy performance was based on area under curve of graph ER and PR, this strategy neither is the best nor the worst strategy on FVC2000 DB2A and FVC2000 DB3A, while on FVC2002 DB1A it outperfomed the others and even it gave impressive results for index created by three impressions per finger (with or without NT) by ideal step down curve where PR equal to 1% can always be maintained for smaller ER.DOI:http://dx.doi.org/10.11591/ijece.v4i5.658
Tpda2 Algorithm for Learning Bn Structure From Missing Value and Outliers in Data Mining
Three-Phase Dependency Analysis (TPDA) algorithm was proved as most efficient algorithm (which requires at most O(N4) Conditional Independence (CI) tests). By integrating TPDA with "node topological sort algorithm", it can be used to learn Bayesian Network (BN) structure from missing value (named as TPDA1 algorithm). And then, outlier can be reduced by applying an "outlier detection & removal algorithm" as pre-processing for TPDA1. TPDA2 algorithm proposed consists of those ideas, outlier detection & removal, TPDA, and node topological sort node
Algorithms of Clustering and Classifying Batik Images Based on Color, Contrast and Motif
An interactive system could be provided for batik customers with the aim of helping them in selecting the right batiks. The system should manage a collection of batik images along with other information such as fashion color type, the contrast degree, and motif. This research aims to find methods of clustering and classifying batik images based on fashion color, contrast and motif. A color clustering algorithm using HSV color system is proposed. Two algorithms for contrast clustering, both utilize wavelet, are proposed. Six algorithms for clustering and classifying batik images based on group of motifs, employing shape- and texture-based techniques, are explored and proposed. Wavelet is used in image pre-processing, Canny detector is used to detect image edges. Experiments are conducted to evaluate the performance of the algorithms. The result of experiments shows that fashion color and contrast clustering algorithms perform quite well. Three of motif based clustering and classification algorithms perform fairly well, further work is needed to increase the accuracy and to refine the classification into detailed motif
Integrasi Algoritma Pohon Keputusan C4.5 Yang Dikembangkan Ke Dalam Object-relational Dbms
Integrasi teknik-teknik data mining ke dalam DBMS, khususnya Object-Relational DBMS (ORDBMS), masih merupakan bidang penelitian yang aktif. Isu utama pada integrasi ini adalah: peleburan algoritma data mining ke dalam ORDBMS dengan memanfaatkan fitur-fiturnya untuk memperbaiki kualitas teknik tersebut. Pada penelitian ini, algoritma klasifikasi C4.5 dikembangkan dengan pendekatan aljabar relasional dan diintegrasikan ke dalam ORDBMS sebagai prosedur-prosedur tersimpan Java dan berbasis SQL, dengan tujuan untuk meningkatkan skalabilitas dan efisiensinya. Hasil eksperimen menunjukkan bahwa algoritma yang sudah diintegrasikan berhasil memperbaiki skalabilitas dan pada kasus khusus juga memperbaiki efisiensi
Systemic Glutathione as a Skin-Whitening Agent in Adult
Objectives. To compare the efficacy and safety profiles of systemic glutathione as a skin-whitening agent in adults from several randomized controlled trials (RCTs). Methods. This study is an evidence-based case report with literature search conducted on Clinical Key, Cochrane, Journal of the American Academy of Dermatology, Taylor and Francis Online, ScienceDirect, and PubMed databases. Three relevant RCTs were extracted and assessed for validity, importance, and applicability. Results. From 3 included trials, one of the studies opposed glutathione as a skin-whitening agent. However, the other two showed significant results only to some parts of the body or to certain age groups. As a skin-whitening agent, studies showed that glutathione yielded other cosmetic benefits as it may improve skin elasticity and reduce skin wrinkles. Furthermore, glutathione was well tolerated in oral preparations, but not in parenteral preparations. Conclusions. Highest-evidence literatures showed that glutathione is not beneficial enough as a skin-whitening agent as it was only effective in some parts of the body and did not elicit long-lasting effects. However, its safety profiles in oral preparations were well tolerated. More researches regarding the time needed for skin color to return to its original state following drug withdrawal need to be conducted as it is yet to be discovered