Browsing by Author "Jing, Min-Quan"

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A NEW STEGANOGRAPHY METHOD VIA VARIOUS ANIMATION TIMING EFFECTS IN POWERPOINT FILES
(2009)
Jing, Min-Quan
;
Yang, Wen-Chao
;
Chen, Ling-Hwei
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資訊工程學系
;
Department of Computer Science
In this paper, a new steganography method that hides message via various animation timing effects in a PowerPoint file is proposed. The animation effects are designed for the presenter to emphasis the key points, control the flow or enrich the interesting in presentation. Then the animation timing effect is the speed, time and repeat control part of animation effect. It is worth mentioning that adding animation effects does not change any content of the slides in the PowerPoint file. In contrast to other steganography methods, using various animation effects to hide message not only livens up on-screen presentations, but also keeps the real content of the PowerPoint file intact.
A NOVEL METHOD FOR HORIZONTAL EYE LINE DETECTION UNDER VARIOUS ENVIRONMENTS
(2010-05-01)
Jing, Min-Quan
;
Cheny, Ling-Hwei
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資訊工程學系
;
Department of Computer Science
The eye line is defined to be a horizontal line passing the two eyes of a human face. It can be used to help locate the true positions of eyes and face. In this paper, we propose a method to extract the horizontal eye line of a face under various environments. Based on the facts that the eye color is very different from skin color and the gray level variance of an eye is high, some eye-like regions are first located. Then the horizontal eye line is extracted based on the located eye-like regions and some geometric properties in a face. Experimental results are given to show that the proposed method is robust under a wide range of lighting conditions, different poses and races. The detection rate for HHI face database is 95.63%. For Champion face database, the detection rate is 94.27%.
A NOVEL METHOD FOR SHOEPRINTS RECOGNITION AND CLASSIFICATION
(2009)
Jing, Min-Quan
;
Ho, Wei-Jong
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Chen, Ling-Hwei
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資訊科學與工程研究所
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Institute of Computer Science and Engineering
In this paper, we present a method for automatically classifying/recognizing the shoeprint images based on the outsole pattern. Shoeprints are distinctive patterns often found at crime scenes that can provide valuable forensic evidence. Directionality is the most obvious feature in these shoeprints. For extracting features corresponding to the directionality, co-occurrence matrices, Fourier transform, and a directional matrix are applied to the shoeprint image. With the stage of principal component transform, the method is invariant to rotation and translation variance. Experimental results demonstrate the performance of the method.
A REAL-TIME UNUSUAL VOICE DETECTOR BASED ON NURSING AT HOME
(2009)
Jing, Min-Quan
;
Wang, Chao-Chun
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Chen, Ling-Hwei
;
資訊工程學系
;
Department of Computer Science
In this paper, we will propose a method to detect an unusual voice for nursing system. Based on the healthy condition of a person, we define four kinds of unusual voices including cough, groan, wheeze and cry for help. When the person nursed sends out the unusual voices, we judge that his health condition have a doubt, and need someone to pay attention. In order to detect the unusual voices, we extract five features on audio waveform, including the number of segmented parts, duration of waveform, mean of volume, zero crossing rate and correlation. Experimental results show that the detection rate is 94%similar to 97% for these four kinds of unusual voices. In false alarm, there are only 0.08% of wrong rates.
Novel face-detection method under various environments
(2009-06-01)
Jing, Min-Quan
;
Chen, Ling-Hwei
;
資訊工程學系
;
Department of Computer Science
We propose a method to detect a face with different poses under various environments. On the basis of skin color information, skin regions are first extracted from an input image. Next, the shoulder part is cut out by using shape information and the head part is then identified as a face candidate. For a face candidate, a set of geometric features is applied to determine if it is a profile face. If not, then a set of eyelike rectangles extracted from the face candidate and the lighting distribution are used to determine if the face candidate is a nonprofile face. Experimental results show that the proposed method is robust under a wide range of lighting conditions, different poses, and races. The detection rate for the HHI face database is 93.68%. For the Champion face database, the detection rate is 95.15%. (C) 2009 Society of Photo-Optical Instrumentation Engineers. [DOI: 10.1117/1.3156843]
SOLVING JAPANESE PUZZLES WITH LOGICAL RULES AND DEPTH FIRST SEARCH ALGORITHM
(2009)
Jing, Min-Quan
;
Yu, Chiung-Hsueh
;
Lee, Hui-Lung
;
Chen, Ling-Hwei
;
資訊工程學系
Japanese puzzle is one of logical games popular in Japan and Netherlands. Solving Japanese puzzle is a NP-complete problem. There are some related papers proposed. Some use genetic algorithm (GA), but the solution may be wrong. Some use depth first search (DFS) algorithm, which is an exhaustive search, the execution speed is very slow. In this paper, we propose a puzzle solving algorithm to treat these problems. Based on the fact that most of Japanese puzzle are compact and contiguous, some logical rules are deduced to paint some cells. Then, the DFS algorithm with the "branch and bound" scheme, which is used to do early termination for those impossible paths, is used to solve those undetermined cells. Experimental results show that our algorithm can solve Japanese puzzles successfully, and the processing speed is significantly faster than that of DFS.