Yea-Shuan
Yea-Shuan Huang, Zhugong Town TW
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20080240500 | IMAGE PROCESSING METHODS - A method of image processing, the method comprising receiving an image frame including a plurality of pixels, each of the plurality of pixels including an image information, conducting a first extraction based on the image information to identify foreground pixels related to a foreground object in the image frame and background pixels related to a background of the image frame, scanning the image frame in regions, identifying whether each of the regions includes a sufficient number of foreground pixels, identifying whether each of regions including a sufficient number of foreground pixels includes a foreground object, clustering regions including a foreground object into at least one group, each of the at least one group corresponding to a different foreground object in the image frame, and conducting a second extraction for each of at least one group to identify whether a foreground pixel in the each of the at least one group is to be converted to a background pixel. | 10-02-2008 |
Yea-Shuan Huang, Hsinchu City TW
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20110280488 | Method and system for image extraction and identification - The present invention provides a method for extracting an image texture signal, a method for identifying image and a system for identifying an image. The method for extracting an image texture signal comprises the following steps: extracting a first image signal; employing a first operation procedure to the first image signal to obtain a second image signal; employing a second operation procedure to the second image signal to obtain a third image signal; employing a third operation procedure to the third image signal to obtain a fourth image signal; outputting the fourth image signal. Therefore, the first image signal is transformed to the fourth image signal via the method for extracting an image texture signal. | 11-17-2011 |
Yea-Shuan Huang, Hsinchu County TW
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20120169895 | METHOD AND APPARATUS FOR CAPTURING FACIAL EXPRESSIONS - A method and an apparatus for capturing facial expressions are provided, in which different facial expressions of a user are captured through a face recognition technique. In the method, a plurality of sequentially captured images containing human faces is received. Regional features of the human faces in the images are respectively captured to generate a target feature vector. The target feature vector is compared with a plurality of previously stored feature vectors to generate a parameter value. When the parameter value is higher than a threshold, one of the images is selected as a target image. Moreover, a facial expression recognition and classification procedures can be further performed. For example, the target image is recognized to obtain a facial expression state, and the image is classified according to the facial expression state. | 07-05-2012 |
Yea-Shuan Huang, Hsinchu TW
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20130259302 | Method of tracking objects - A method of object tracking is provided with creating areas of a tracking object and a non-tracking object respectively; determining a state of the tracking object and the non-tracking object is separation, proximity, or overlap; creating at least one separation template image of a separation area of the tracking object and/or the non-tracking object if the tracking object is proximate the non-tracking object; fetching all feature points of an overlapping area of the tracking object and the non-tracking object if the tracking object and the non-tracking object overlap; performing a match on each of the feature points and the separation template image so as to calculate a corresponding matching error score respectively; and comparing the matching error score of each feature point with that of the separation template image so as to determine whether the feature points belong to the tracking object or the non-tracking object. | 10-03-2013 |
20130259324 | Method for face recognition - A method for face recognition is provided with collecting a match facial image; retrieving a reference image from image records of a database or an input image; selecting one or more facial features from each of the match facial image and the reference image; obtaining at least one match facial feature and a match deviation of the reference image corresponding to the facial features of the match facial image; creating a match geometric model and a reference geometric model; obtaining a model deviation by comparing the match geometric model and the reference geometric model; and employing a match deviation and a model deviation to obtain a recognition score based on a predetermined rule. The method involves a two-way face recognition by integrating facial features of block matching with geometric model comparison. It employs relationship of match deviation and model deviation. | 10-03-2013 |