Abstract: A smart motion detection device with a determining method includes a memory, a processor, and a sensor array coupled to the memory and the processor. An image captured by the sensor array is processed by the processor. The sensor array is adapted to pre-store the image into the memory when the processor is operated in the sleep mode, and the pre-stored image is transmitted to the processor when the processor is operated in the wakeup mode. The sensor array includes a comparator adapted to generate an alarm signal for switching the processor from the sleep mode to the wakeup mode in accordance with a comparison result of the pre-stored image. The determining method includes the processor analyzing images captured by the sensor array when the sensor array is activated to capture the images, and the processor analyzing images pre-stored inside the memory when the sensor array is not activated.

Abstract: An image sensing method, comprising: (a) controlling an image sensor to apply a first frame rate to sense a first frame during a first frame period; (b) determining exposure variation in the first frame period; and (c) during one of the first frame period and a second frame period following the first frame period, switching the image sensor to apply a second frame rate different from the first frame rate to sense at least one third frame, when the step (b) determines the exposure variation exceeds a threshold level. A related image sensing system is also disclosed. Via such image sensing method, the frame switch delay of a conventional frame switch can be reduced.

Abstract: A motion detection device is matched with a passive detector utilized to detect an object and to accordingly generate a triggering signal. The motion detection device includes an image capturing unit and an operating processor. The operating processor is electrically connected with the image capturing unit, the operating processor is adapted to switch the image capturing unit from a sleep mode to a wakeup mode for motion detection while being triggered by the triggering signal, and further to optionally actuate an external host in accordance with an analysis result of the motion detection. A motion detection method applied to the motion detection device includes receiving the triggering signal, switching the image capturing unit to the wakeup mode for capturing the first monitoring image, analyzing the first monitoring image to determine existence of the object, and actuating the external host in accordance with an analysis result of the first monitoring image.

Abstract: A smart motion detection device with a determining method includes a memory, a processor, and a sensor array coupled to the memory and the processor. An image captured by the sensor array is processed by the processor. The sensor array is adapted to pre-store the image into the memory when the processor is operated in the sleep mode, and the pre-stored image is transmitted to the processor when the processor is operated in the wakeup mode. The sensor array includes a comparator adapted to generate an alarm signal for switching the processor from the sleep mode to the wakeup mode in accordance with a comparison result of the pre-stored image. The determining method includes the processor analyzing images captured by the sensor array when the sensor array is activated to capture the images, and the processor analyzing images pre-stored inside the memory when the sensor array is not activated.

Abstract: A motion detection device is matched with a passive detector utilized to detect an object and to accordingly generate a triggering signal. The motion detection device includes an image capturing unit and an operating processor. The operating processor is electrically connected with the image capturing unit, the operating processor is adapted to switch the image capturing unit from a sleep mode to a wakeup mode for motion detection while being triggered by the triggering signal, and further to optionally actuate an external host in accordance with an analysis result of the motion detection. A motion detection method applied to the motion detection device includes receiving the triggering signal, switching the image capturing unit to the wakeup mode for capturing the first monitoring image, analyzing the first monitoring image to determine existence of the object, and actuating the external host in accordance with an analysis result of the first monitoring image.

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 an image sensor including a light sensitive device and a digital signal processing circuit. The light sensitive device is configured to output a digital image. The digital signal processing circuit is configured to detect at least one feature point in the digital image and calculate a feature point coordinate of the at least one feature point.

Abstract: An image sensing module utilizes an image sensor to sense objects and a mirror image of the objects in a mirror through a plurality of first light filtering components with a first transmission spectrum and a plurality of second light filtering components with a second transmission spectrum for generating an image. A light filtering module substantially having the first transmission spectrum is disposed in front of the mirror. The image includes a plurality of pixels. Each pixel includes a first sub data and a second sub data. The image sensing module utilizes an image sensing controller to detect real images corresponding to the objects and virtual images correspond to the mirror image of the objects from the image according to the first sub data and the second sub data of the plurality of pixels.

Abstract: An image denoising method includes the steps of: sequentially selecting a pixel in an image as a current pixel; dynamically determining a current search block and a strength parameter; pre-denoising the comparison block of each pixel in the current search block; comparing the comparison block of the pre-denoised neighborhood pixel and the comparison block of the pre-denoised current pixel to obtain a similarity between each neighborhood pixel and the current pixel in the current search block; determining a weighting of each neighborhood pixel related to the current pixel according to the strength parameter, and a distance and the similarity between each neighborhood pixel and the current pixel in the current search block; and weighted averaging each neighborhood pixel and the current pixel in the current search block according to the weighting to obtain a reconstruction value of the current pixel.

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: There is provided an image sensor including a light sensitive device and a digital signal processing circuit. The light sensitive device is configured to output a digital image. The digital signal processing circuit is configured to detect at least one feature point in the digital image and calculate a feature point coordinate of the at least one feature point.

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: An image denoising method according to the present invention includes the steps of: sequentially selecting a pixel in an image as a current pixel; dynamically determining a current search block and a strength parameter; transferring the comparison block of each pixel in the current search block to a frequency domain; determining a current frequency basis; obtaining a similarity between each neighborhood pixel and the current pixel in the current search block according to the current frequency basis; determining a weighting of each neighborhood pixel related to the current pixel according to the strength parameter, and a distance and the current pixel in the current search block; and weighted averaging each neighborhood pixel and the current pixel in the current search block according to the weighting so as to obtain a reconstruction value of the current pixel.

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: 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: An image sensing module utilizes an image sensor to sense objects and a mirror image of the objects in a mirror through a plurality of first light filtering components with a first transmission spectrum and a plurality of second light filtering components with a second transmission spectrum for generating an image. A light filtering module substantially having the first transmission spectrum is disposed in front of the mirror. The image includes a plurality of pixels. Each pixel includes a first sub data and a second sub data. The image sensing module utilizes an image sensing controller to detect real images corresponding to the objects and virtual images correspond to the mirror image of the objects from the image according to the first sub data and the second sub data of the plurality of pixels.

Abstract: An image capturing device includes an image capturing unit, a processing unit, a register unit, and at least one triggering unit. The image capturing unit is used for capturing image data; the processing unit is electrically connected to the image capturing unit and is used for executing a comparison procedure; the register unit is electrically connected to the processing unit and is configured with a determination logic; and the triggering unit is electrically connected to the processing unit, in which the processing unit runs the comparison procedure according to at least one of an execution state of the triggering unit and the determination logic, and the processing unit controls an operation mode of the image capturing device according to the comparison procedure.

Abstract: An image denoising method includes the steps of: sequentially selecting a pixel in an image as a current pixel; dynamically determining a current search block and a strength parameter; pre-denoising the comparison block of each pixel in the current search block; comparing the comparison block of the pre-denoised neighborhood pixel and the comparison block of the pre-denoised current pixel to obtain a similarity between each neighborhood pixel and the current pixel in the current search block; determining a weighting of each neighborhood pixel related to the current pixel according to the strength parameter, and a distance and the similarity between each neighborhood pixel and the current pixel in the current search block; and weighted averaging each neighborhood pixel and the current pixel in the current search block according to the weighting to obtain a reconstruction value of the current pixel.

Abstract: An image denoising method according to the present invention includes the steps of: sequentially selecting a pixel in an image as a current pixel; dynamically determining a current search block and a strength parameter; transferring the comparison block of each pixel in the current search block to a frequency domain; determining a current frequency basis; obtaining a similarity between each neighborhood pixel and the current pixel in the current search block according to the current frequency basis; determining a weighting of each neighborhood pixel related to the current pixel according to the strength parameter, and a distance and the current pixel in the current search block; and weighted averaging each neighborhood pixel and the current pixel in the current search block according to the weighting so as to obtain a reconstruction value of the current pixel.

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.