Authentications of Myanmar National Registration Card

The automatic identification system of Myanmar national registration card (NRC) holder is presented in this paper. The proposed system can be handled the identification by the extracted low quality face image and fingerprint image from Myanmar NRC. Both of the facial recognition and fingerprint recognition system are developed for Myanmar citizenship confirmation. Age invariant face recognition algorithm is performed based on combination of DiaPCA (Diagonal principal Component Analysis) and KNN (Kth nearest neighbor classifier) approaches. An algorithm of the fingerprint recognition is proposed for recognition of the poor quality fingerprint image with fabric background.  Several experiments have been done for confirming the effectiveness of the proposed approach

Survey on Emotion Recognition Using Facial Expression

Automatic recognition of human affects has become more interesting and challenging problem in artificial intelligence, human-computer interaction and computer vision fields. Facial Expression (FE) is the one of the most significant features to recognize the emotion of human in daily human interaction. FE Recognition (FER) has received important interest from psychologists and computer scientists for the applications of health care assessment, human affect analysis, and human computer interaction. Human express their emotions in a number of ways including body gesture, word, vocal and facial expressions. Expression is the important channel to convey emotion information of different people because face can express mainly human emotion. This paper surveys the current research works related to facial expression recognition. The study attends to explored details of the facial datasets, feature extraction methods, the comparison results and futures studies of the facial emotion system

A Fast Image-Spam Filtering System using Support Vector Machine

The explosion of Image spam emails hasprompted the development of numerous spamfiltering techniques. This paper proposes anefficient image spam filtering system using threemethods. The first method, File properties,analyses high level features in order to reducecomputation cost. The second approach usesHue, Saturation, Intensity (HSI) color model ofhistogram and the third method uses Hough lineDetection. These three methods filter the imagespam by analyzing both images including textand image. The images are collected from threedifferent datasets that are Priceton, Image SpamHunter and Spam Archieve Datasets. SupportVector Machine (SVM) classifies the input imageis spam image or normal image. Theexperimental result shows the accuracy ofdifferent methods on different datasets andevaluates computation time. Among the threemethods, Hough line can detect the input imagewithin the minimum processing time required

Divisive Hierarchical Clustering of Drugs Based on Chemical Compositions

Clustering is the process of grouping the data into classes or clusters. Objects within a class have high similarity in comparison to one another, but are very dissimilar to objects in other clusters. In this paper we intend to cluster drugs based on their chemical composition so that users can know which drug on which cluster is composed of what chemicals by which composition. We will implement this system by using a hierarchical divisive monothetic clustering, called DIVICLUS_T. It allows becoming a decision tree of the hierarchy. This paper gives the valuable information of drugs for drug- researchers

Fingerprint Recognition System based on Orientation and Texture Features

Fingerprint recognition is one of the mostwell-known and publicized biometrics forpersonal identification. Fingerprints exhibitoriented texture-like patterns. The textureinformation of the fingerprint can be used forfingerprint matching. Gabor filters can optimallycapture global and local texture informationeven from poor-quality or incomplete images.But Gabor filterbank-based approach use onlytexture information for fingerprint recognitionand it is not robust to image distortion androtation. In this paper, a hybrid fingerprintmatching algorithm is developed for identifyingthe low quality fingerprint images by combiningorientation features and the local texture patternobtained using a bank of Gabor filters. Theproposed matching approach is compared withthe filterbank-based approach, and the proposedsystem produces a much improved matchingperformance by combining the orientationfeatures to the filterbank-based features

Fingerprint Recognition System for Personal Identification

Fingerprints are widely used in biometrictechniques for automatic personal identificationwork. In this paper, a fingerprint recognition systemis developed to identify a person according tofingerprint image on Myanmar National RegistrationCards (NRCs). Generally, fingerprint identificationapproaches are minutiae-based and texture-based.Although the minutiae-based method is popular andextensively used method for fingerprintidentification, it shows poor performance for lowquality images. In proposed system, the texturebasedapproach for fingerprint recognition usingDiscrete Wavelet Transform (DWT) is developed. Toreduce the search time and computationalcomplexity, the proposed system classifies thefingerprint types according to ridges direction bysingular candidate analysis using an extendedrelational graph. And then, the system finds the localfeatures of the fingerprint using DWT and it iscompared to the subset of the database containingthat type of fingerprints using Euclidean distancemetric. The performance of the proposed system canbe evaluated by measuring its False Reject Rate(FRR) and False Accept Rate (FAR). Theeffectiveness of the proposed system can beconfirmed through the experimental results