• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.13 no.4
• /
• pp.91-97
• /
• 2013

A finger-gesture remote controller using the single camera is implemented in this paper, which is base on the recognition of finger number and finger moving direction. Proposed method uses the transformed YCbCr color-difference information to extract the hand region effectively. The number and position of finger are computer by using a double circle tracing method. Specially, a user continuous-command can be performed repeatedly by recognizing the finger-gesture direction of single shape. The position information of finger enables a user command to amplify a same command in the User eXperience. Also, all processing tasks are implemented by using the Intel OpenCV library and C++ language. In order to evaluate the performance of the our proposed method, after applying to the commercial video player software as a remote controller. As a result, the proposed method showed the average 89% recognition ratio by the user command-mode.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.28-30
• /
• 2021

In this paper, an algorithm that detects the user's finger direction using the YOLO (You Only Look Once) library was proposed. The processing stage of the proposed finger direction detection algorithm consists of a learning data management stage, a data learning stage, and a finger direction detection stage. As a result of the experiment, it was found that the distance between the camera and the finger had a very large influence on the accuracy of detecting the direction of the finger. We plan to apply this function to Turtlebot3 after improving the accuracy and reliability of the proposed algorithm in the future.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.9
• /
• pp.77-85
• /
• 2015

The finger language is the part of the sign language, which is a language system that expresses vowels and consonants with hand gestures. Korean finger language has 31 gestures and each of them needs a lot of learning models for accurate recognition. If there exist mass learning models, it spends a lot of time to search. So a real-time awareness system concentrates on how to reduce search spaces. For solving these problems, this paper suggest a hierarchy HMM structure that reduces the exploration space effectively without decreasing recognition rate. The Korean finger language is divided into 3 categories according to the direction of a wrist, and a model can be searched within these categories. Pre-classification can discern a similar finger Korean language. And it makes a search space to be managed effectively. Therefore the proposed method can be applied on the real-time recognition system. Experimental results demonstrate that the proposed method can reduce the time about three times than general HMM recognition method.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.10
• /
• pp.4126-4142
• /
• 2015

Finger vein recognition is a biometric technology using finger veins to authenticate a person, and due to its high degree of uniqueness, liveness, and safety, it is widely used. The traditional Symmetric Local Graph Structure (SLGS) method only considers the relationship between the image pixels as a dominating set, and uses the relevant theories to tap image features. In order to better extract finger vein features, taking into account location information and direction information between the pixels of the image, this paper presents a novel finger vein feature extraction method, Multi-Orientation Weighted Symmetric Local Graph Structure (MOW-SLGS), which assigns weight to each edge according to the positional relationship between the edge and the target pixel. In addition, we use the Extreme Learning Machine (ELM) classifier to train and classify the vein feature extracted by the MOW-SLGS method. Experiments show that the proposed method has better performance than traditional methods.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.5
• /
• pp.1766-1784
• /
• 2014

Finger vein images contain rich oriented features. Local line binary pattern (LLBP) is a good oriented feature representation method extended from local binary pattern (LBP), but it is limited in that it can only extract horizontal and vertical line patterns, so effective information in an image may not be exploited and fully utilized. In this paper, an orientation-selectable LLBP method, called generalized local line binary pattern (GLLBP), is proposed for finger vein recognition. GLLBP extends LLBP for line pattern extraction into any orientation. To effectually improve the matching accuracy, the soft power metric is employed to calculate the matching score. Furthermore, to fully utilize the oriented features in an image, the matching scores from the line patterns with the best discriminative ability are fused using the Hamacher rule to achieve the final matching score for the last recognition. Experimental results on our database, MMCBNU_6000, show that the proposed method performs much better than state-of-the-art algorithms that use the oriented features and local features, such as LBP, LLBP, Gabor filter, steerable filter and local direction code (LDC).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2019.05a
• /
• pp.167-168
• /
• 2019

Lately, variety of algorithms using encryption technology has been adopted as methods of unlocking smartphone. It is advancing toward the direction to solve through human biometrics technology which has already succeeded in commercialization. These include finger print recognition, face recognition, and iris recognition. In this study, we selected biometrics recognition technology and pattern recognition and password input methods which are already commercialized as evaluation items. The evaluation items are five algorithms including finger print recognition, face recognition iris recognition, pattern recognition and password input method. Based on these algorithms, analytic hierarchy process is used to analyze the preference of smartphone users. Also, the theoretical implications are presented based on the analysis results.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.23 no.10
• /
• pp.1228-1233
• /
• 2019

Recently, a variety of algorithms using encryption technology have been adopted as methods of unlocking smartphone. It is advancing toward the direction to solve the unlocking problem through human biometrics technology, which has already succeeded in commercializing. These include finger print recognition, face recognition, and iris recognition. In this study, the evaluation items are five algorithms, including finger print recognition, face recognition, iris recognition, pattern recognition, and password input method. Based on the algorithms adopted, the AHP (analytic hierarchy process) technique was used to calculate the preferred priorities for smartphone users. Finger print recognition ( .400) was the top priority for smartphone users. Next, pattern recognition ( .237) was placed in the second priority for smartphone users. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.15 no.1
• /
• pp.139-146
• /
• 2020

The disadvantage of the general robot cleaner is that it works only on the designated route, so it is impossible to clean the place outside the designated route. Therefore, in this study, the direction control methodology for searching the place other than the designated route based on the finger recognition technology was studied to compensate for the shortcomings of the existing cleaner. Raspberry Pi was used as the main controller and Open CV program was used to recognize the number of fingers. To verify the validity of the proposed methodology, a finger recognition algorithm was implemented using Python language, and as a result of adopting the Logitech C922, the success rate was 100% at 90cm and 70% at 110cm, respectively.

• The Journal of the Korea Contents Association
• /
• v.12 no.12
• /
• pp.517-523
• /
• 2012

Biometrics is a study of identifying individual by using the features of human body. It has been studied for an alternative or complementary method for the classical method based on password, ID card, etc. In comparison with the fingerprint, iris, ear, palmprint, finger-knuckle print has been recently studied. This paper proposes an effective method for recognizing finger-knuckle print based on the feature of Gradient orientation. The main features of finger-knuckle print are the size and direction of winkles. In order to extract these features stably, we make a feature vector consisted of Gradient orientations after the preprocessing of enhancing non-uniform brightness and low contrast. Total 790 images acquired from 158 persons have been used at the experiment for evaluating the performance of the proposed method. The experimental results show the recognition rate of 99.69% and the relatively high decidability index of 1.882. These results demonstrate that the proposed method is effective in recognizing finger-knuckle print.

• Journal of the Institute of Convergence Signal Processing
• /
• v.15 no.2
• /
• pp.42-47
• /
• 2014

A finger-gesture game controller using the single camera is implemented in this paper, which is based on the recognition of the number of fingers and the index finger moving direction. Proposed method uses the CAMShift algorithm to trace the end-point of index finger effectively. The number of finger is recognized by using a double circle tracing method. Then, HSI color mode transformation is performed for the CAMShift algorithm, and YCbCr color model is used in the double circle tracing method. Also, all processing tasks are implemented by using the Intel OpenCV library and C++ language. In order to evaluate the performance of the proposed method, we developed a shooting game simulator and validated the proposed method. The proposed method showed the average recognition ratio of more than 90% for each of the game command-mode.