Purahong, Boonchana

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Purahong, Boonchana
Alternative Name
Purahong, B.
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boonchana.pu@kmitl.ac.th

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    Item type:Publication,
    Biometrics based on facial landmark with application in person identification
    (2019-01-01)
    Juhong, Aniwat
    ;
    Purahong, Boonchana
    ;
    Suwan, Supakorn
    ;
    Pitavirooj, Chuchart
    This paper presents a novel technique for face recognition based on facial landmarks extracted automatically. Our landmarks are those associated with eyes mouth and nose. To extract facial landmarks, we first use Haar cascade algorithm to detect the face ROI following by Haar cascade algorithm for the eye, mouth and nose ROI determination. To find landmark associated with the eye, we convert eye ROI image to binary image using thresholding algorithm. To exclude the eyebrow region, we apply horizontal radon transform. The project data will then be used to separate the eyebrow region from the eye region. To detect eye-related landmark, vertical radon transform is applied. With the vertical projection data, the outermost pixel can be identified and the associated eye landmark can be determined. The similar technique can then be used to identify landmarks associated with the nose and mouth area. Given the correspond landmarks on the reference face and the query face, geometric transformation can be determined using normal equation bases on minimized mean squared error. The two faces are then aligned. To provide the quantitative measurement, the two aligned face are converted to edge image using canny edge algorithm. The distance map error between the two aligned edge facial images is then used to identify the query face. The purposed algorithm for person identification was tested on the face database resulting in a very high accuracy.
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    Item type:Publication,
    Medical Drone Managing System for Automated External Defibrillator Delivery Service
    (2022-04-01)
    Purahong, Boonchana
    ;
    Anuwongpinit, Thanavit
    ;
    Juhong, Aniwat
    ;
    Kanjanasurat, Isoon
    ;
    Pintaviooj, Chuchart
    One of the common causes of a heart attack is fibrillation, a condition that causes an irregular and often abnormally fast heart rate. There is scientific evidence that the survival rate of sudden cardiac arrest patients who are rescued with cardiopulmonary resuscitation (CPR) and with the use of an automated external defibrillator (AED) is significantly increased. Despite the recommendation that automated external defibrillators should be installed in the workplace, along with a proper management system and training for employees on how to use the device, less than 70% of non-residential areas have an AED installed. The situation is even worse in residential areas, with less than 30% having an AED installed. This research concerns the development of a medical drone managing system that can deliver an AED in case of emergency. An application was developed that can be installed on the mobile phone and/or tablet of the patient or the accompanying person. In the event of a heart attack, the patient or the accompanying person can call a medical drone by sending coordinates to the drone station and a notification to medical staff. The drone station administrator can respond by sending the drone, which automatically lands at the patient’s location. After being tested in a simulation situation, the operational field test yielded satisfactory results. The medical drone can land within 1.5 meters of the destination. The designed AED drone can be used not only to deliver AEDs, but also first aid kits and prescribed drugs suitable for medical care. Such a system is especially useful in the current context of the COVID‐19 pandemic.