Abstract: The present invention discloses a gesture detecting apparatus which includes an image capturing device and a processing unit. The image capturing device is for capturing an object light beam reflected by an object and outputting corresponding image information accordingly. The processing unit is for processing the image information and generating a first command or a second command accordingly. The steps of generating the first command and the second command by the processing unit include: outputting a first command if an image size of the image information increases with a relatively higher velocity and decreases with a relatively lower velocity in a sequential time series; and outputting a second command if the image size of the image information increases with a relatively lower velocity and decreases with a relatively higher velocity in the sequential time series.

Abstract: The present invention relates to a background model update method for image process. The accuracy of distinguishing a foreground image from the background model can be improved by adjusting the background model update level according to image variations such as brightness variation, motion variation, color variation, etc.

Abstract: A displacement detection device includes a light source, an image sensor and a processing unit. The light source is configured to illuminate a work surface. The image sensor is configured to capture reflected light from the work surface and to output an image frame. The processing unit is configured to select a window of interest in the image frame having a maximum image feature and to calculate a displacement of the displacement detection device according to the window of interest.

Abstract: The present invention discloses a method for outputting a command by detecting a movement of an object, which includes the following steps. First, an image capturing device captures images generated by the movement of the object at different timings by. Next, a motion trajectory is calculated according to the plurality of images. Further next, a corresponding command is outputted according to the motion trajectory. The present invention also provides a system which employs the above-mentioned method.

Abstract: A computer readable media having at least one program code recorded thereon. An interference image determining method can be performed when the program code is read and executed. The interference image determining method comprises: (a) controlling a light source to illuminate an object on a detecting surface to generate an image; (b) controlling a sensor to catch a current frame of the image; (c) utilizing an image characteristic included in the current frame to determine a interference image part of the current frame; and (d) updating a defined interference image according to the determined interference image part.

Abstract: There is provided a displacement detection device including an image sensor, a light source, a light control unit and a processing unit. The image sensor captures image frames at a sampling frequency. The light source provides, in a speed mode, light for the image sensor in capturing the image frames. The light control unit controls the light source with the speed mode to turn on at a lighting frequency or to turn off serially. The processing unit calculates a displacement according to the image frames captured when the light source turns on to be served as an estimated displacement for an interval during which the light source turns off. There is further provided an operating method of a displacement detection device.

Abstract: A human face recognition method and apparatus are provided. A processor of the human face recognition apparatus calculates red, green, and blue component statistic information for each of a plurality of human face images. The processor uses an independent component analysis algorithm to analyze component statistic information of two colors and derive a piece of first component information and a piece of second component information. The processor transforms the pieces of first component information and second component information into a frequency domain to derive a piece of first frequency-domain information and a piece of second frequency-domain information. The processor calculates an energy value of the first frequency-domain information within a frequency range. The energy value is used to decide whether the human face images are captured from a human being.

Abstract: Method for increasing accuracy of heart rate measuring includes sensing a finger of a user for generating sensed images of the finger, obtaining displacement information of the finger according to the sensed images, then using the motion information to compensate the sensed images of the finger, and finally using brightness variation of the compensated sensed images of the finger to measure heart rate of the user.

Abstract: There is provided a click-event detection device including a light source, a light control unit, an image sensor and a processing unit. The light control unit is configured to control the light source to illuminate a finger. The image sensor receives reflected light from the finger to accordingly output a plurality of bright image frames and dark image frames. The processing unit is configured to calculate a differential image characteristic between the bright image frames and the dark image frames, to determine a plurality of operating states according to the differential image characteristic, to count a residence time at each of the operating states, and to identify a click-event according to the operating states and the residence time.

Abstract: A shooting parameter adjustment method for face detection includes (A) acquiring an image; (B) dividing the image into a plurality of blocks, and calculating a brightness value of each of the blocks; (C) selecting at least one of the plurality of blocks, and adjusting a shooting parameter according to the brightness value of the selected block; and (D) acquiring another image according to the shooting parameter, and performing a face detection procedure with the another image. The shooting parameter adjustment method can automatically adjust a shooting parameter of an image capturing device according to brightness of different blocks in an image. Therefore, by using this method, the brightness of a face, no matter being too high or too low, can be adjusted to a value suitable for face detection, so as to improve the accuracy of the face detection procedure.

Abstract: A dynamic image compression method for human face detection includes the following steps. An original image is acquired. The image is divided into a plurality of blocks. A first brightness and a plurality of gradient values of each block are calculated. A second brightness of each block is calculated according to a brightness transformation function and the first brightness. A reconstruction image is generated according to the second brightness and the plurality of gradient values of each block. Human face detection is performed according to the reconstruction image. Therefore, gradient values within an original square are. When the human face detection process is performed through gradient direction information, a success rate of detection is greatly increased.

Abstract: The present invention discloses an input device and an input method. The input device comprises: an image acquiring device for acquire sequence of images when an object moves in front of the field of view of the image acquiring device; and a processor for generating a rotation signal according to the rotation status of the object.

Abstract: An image sensor includes a sensor matrix including a plurality of sensing elements and a plurality of shutter control lines. Each sensing element includes an electronic shutter and a photo-detector, wherein the electronic shutter controls the exposure time of the photo-detector. Each shutter control line couples to a row or column of the electronic shutters, whereby different rows or columns of the electronic shutters can be independently controlled, and the photo-detectors in the same row or column can have the same exposure time.

Abstract: A sensing system includes a complex reflector and an image sensor, in which the complex reflector is disposed on one side of a flat panel. The complex reflector includes a first section and a second section which are stacked, in which the first section provides a mirror image and a real image, and the second section provides a real image. The image sensor is used to capture an image generated by an object when touching a surface of the flat panel, and in the image captured by the image sensor, the object simultaneously generates a first object image in an image region corresponding to the second section and an image region corresponding to the first section, and generates a second object image in the image region corresponding to the first section.

Abstract: Optical touch display system includes a light source, a reflector, an image sensor, and a processing device. The light source emits light to at least one object directly and emits light to the at least one object via the reflector at the same time. Then the image sensor receives light reflected from the at least one object directly and light reflected via the reflector simultaneously to form a set of imaging objects which have similar color parameters on an image. Then the processing device produces a set of still image parameters of the image objects such as gravity centers and border boundaries. Based on the still image parameters, the processing device determines the coordinates of the least one object on the optical touch display.

Abstract: When an object touches a touch panel, a projection light source projects a predetermined image including image information and forms an object image having the image information on a surface of the object. An image sensor captures a reflection image including the object image. Then, an angle is calculated according to an image location of the object in the reflection image and a relative position of predetermined axis, and a distance between the object and the image sensor is calculated by comparing the predetermined image with the location, size and/or phase of the image information of the reflection image so as to determine a coordinate of the object on the touch panel according to the angle and the distance.

Abstract: A human face detection device includes a photosensitive element, a human face detection unit, and a skin color threshold generation unit. The photosensitive element is used for capturing a first image containing a first human face block. The human face detection unit compares the first image with at least one human face feature, so as to detect the first human face block. The skin color threshold generation unit is used for updating a skin color threshold value according to the detected first human face block. The skin color threshold value is used for filtering the first image signal to obtain a candidate region, the human face detection unit compares the candidate region with the at least one human face feature to obtain the first human face block, and the skin color threshold value determines whether the first human face block detected by the human face detection unit is correct.

Abstract: A shooting parameter adjustment method for face detection includes (A) acquiring an image; (B) dividing the image into a plurality of blocks, and calculating a brightness value of each of the blocks; (C) selecting at least one of the plurality of blocks, and adjusting a shooting parameter according to the brightness value of the selected block; and (D) acquiring another image according to the shooting parameter, and performing a face detection procedure with the another image. The shooting parameter adjustment method can automatically adjust a shooting parameter of an image capturing device according to brightness of different blocks in an image. Therefore, by using this method, the brightness of a face, no matter being too high or too low, can be adjusted to a value suitable for face detection, so as to improve the accuracy of the face detection procedure.

Abstract: A dynamic image compression method for human face detection includes the following steps. An original image is acquired. The image is divided into a plurality of blocks. A first brightness and a plurality of gradient values of each block are calculated. A second brightness of each block is calculated according to a brightness transformation function and the first brightness. A reconstruction image is generated according to the second brightness and the plurality of gradient values of each block. Human face detection is performed according to the reconstruction image. Therefore, gradient values within an original square are. When the human face detection process is performed through gradient direction information, a success rate of detection is greatly increased.