Abstract: The present disclosure illustrates an image adjusting system with multiple lens modules and method thereof. The system is adapted for an image capturing device having a zoom lens module and a prime lens module. When the zoom lens module and the prime lens module captures a first image and a second image, the image adjusting system can select a first reference calibration parameter table from multiple first calibration parameter tables, and search a current focus parameter from a focus parameter lookup table according to a current motor step, and then multiply the second image, the first reference calibration parameter table and the current focus parameter to generate a third image. Therefore, the third image has substantially consistent with the first image.

Abstract: An image capturing device and a method for calibrating image deformation thereof are provided. The image capturing device has a first image sensor and a second image sensor and the method includes following steps. A plurality of image groups are captured through the first image sensor and the second image sensor. Each of the image groups includes a first image and a second image, and the image groups include a reference image group. Whether an image deformation occurs on a first reference image and a second reference image in the reference image group is detected. If it is detected that the image deformation occurs on the reference image group, a current calibration parameter is updated according to a plurality of feature point comparison values corresponding to the image groups. The current calibration parameter is used for performing an image rectification on each of the first images and the second images.

Abstract: A method for calibrating image defection of an image capturing device having a first and second lens, a focusing actuator, and a prestored first focusing step-to-focusing distance relation includes the following steps. A plurality of image sets are captured by the first and second lens, where each of the image sets includes a first and second image, and the images sets include a reference image set. It is detected whether the reference image set is defective. When the reference image set is detected to be defective, the first focusing step-to-focusing distance relation is calibrated according to a focusing step and a focusing distance corresponding to each of the image sets, where the focusing step corresponding to each of the image sets is the number of steps that the focusing actuator is required to move the first and second lens to a focusing position to generate each of the image sets.

Abstract: A method for calibrating image deformation of an image capturing device having a first and second lens, a focusing actuator, and a prestored first focusing step-to-focusing distance relation includes the following steps. A plurality of image sets are captured by the first and second lens, where each of the image sets includes a first and second image, and the images sets include a reference image set. It is detected whether the reference image set is deformed. When the reference image set is detected to be deformed, the first focusing step-to-focusing distance relation is calibrated according to a focusing step and a focusing distance corresponding to each of the image sets, where the focusing step corresponding to each of the image sets is the number of steps that the focusing actuator is required to move the first and second lens to a focusing position to generate each of the image sets.

Abstract: An image capturing device and a method for detecting image deformation thereof are provided. The method is for the image capturing device having a first sensor and a second image sensor, and the method includes the following steps. A first image is captured through the first image sensor, and a second image is captured through the second image sensor. A deform detection is performed according to the first and second images so as to obtain a comparison information between the first and second images. Whether a coordinate parameter relationship between the first and second images being varied is determined according to the comparison information, in which the coordinate parameter relationship is associated with a spatial configuration relationship between the first and second image sensors.

Abstract: An auto focus (AF) method adapted to an AF apparatus is provided. The AF method includes following steps. A first image is captured by using the first image sensor. At least one characteristic is detected based on the first image, and whether the characteristic meets a predetermined condition is determined. If the characteristic meets the predetermined condition, a focus depth is calculated according to a three-dimensional (3D) depth information and movement of a first lens of the first sensor is driven according to the focus depth for focusing. If the characteristic does not meet the predetermined condition, the first lens is driven to move for many times to obtain a plurality of contrast values, such that movement of the first lens is driven according to the contrast values for focusing. Additionally, an AF apparatus is provided.

Abstract: An image transfer apparatus and a method thereof comprise: capturing at least one first image, wherein the first image includes at least one face image; performing a face detection to obtain at least one face feature; a database has at least one identification information which comprises at least one face photo and a corresponding communication information; comparing the face feature with the face photo saved in the database; retrieving the corresponding communication information and the identification information corresponding to the face photo, if the face feature matches the face photo; performing the face image processing corresponding to the identification information in the first image, so as to obtain at least one second image; transmitting each second image according to the communication information of the processed face image in the second image.

Abstract: The present invention discloses a license plate image-pickup device and an image exposure adjustment method thereof. The license plate image-pickup device comprises an image-sensing module, a recognition module and a processing module. The license plate image-pickup device takes a scene. The image-sensing module senses the scene to produce an image. The recognition module detects a vehicle object. The processing module adjusts the exposure of the vehicle object to produce an exposure adjusted vehicle object, and then the recognition module detects a license plate object from the exposure adjusted vehicle object, and the processing module adjusts the exposure of the license plate object.

Abstract: This invention discloses an image capture device and an image synthesis method thereof. The image capture device comprises an image pickup module and a processing module. The image pickup module scans a plurality of visual angles of a scene in advance to obtain a plurality of temporary images. Each of the temporary images has a scanning focal length value. The processing module analyzes the plurality of temporary image of each of the visual angles to obtain a temporary focal length value. The processing module obtains a weighting focal length value by each temporary focal length value by using a function to control the image pickup module in order to perform a panorama image capturing process according to the weighting focal length value.

Abstract: This invention discloses an image pickup device and an image synthesis method thereof The image pickup device comprises an image-pickup module, an image-synthesis module, a database and a processing module. The image-pickup module captures a plurality of temporary images of a scene. The image-synthesis module extracts a part of each temporary image and combines the parts to form a panorama temporary image, and splits the panorama temporary image into a plurality of zone-areas according to at least one threshold value and a panorama luminosity histogram. The database stores a lookup table for recording a plurality of exposure values. The plurality of the exposure values correspond to luminance values of the zone-areas respectively. The processing module obtains the plurality of exposure values corresponding to the luminance values and obtains a weighting-exposure value by an equation, and controls the image-pickup module to capture the panorama image according to the weighting-exposure value.

Abstract: A method of detecting the subject of an image and imaging device thereof are disclosed. The method comprises the following steps of providing an image capturing module to capture the temporal image, providing the image processing module to receive the temporal image and to determine a plurality of objects from the temporal image, using the image processing module to define a plurality of regions on the temporal image based on the center of temporal image, using the image processing module to assign an initial setup value to each of the objects according to the region corresponding to each of the objects, using the imaging processing module to execute an operation to increase or decrease each of the initial setup values, using the image processing module to execute a sorting, and selecting at least one of the objects as a subject of the temporal image.

Abstract: An image processing method is provided and includes the following steps. A source image arranged in a Bayer pattern is captured. A first-order image process is performed on the source image to produce a first image in YCbCr format. A second-order image process is performed on the source image to produce a second image in YCbCr format. Then, a noise-reducing process is performed on the first image in YCbCr format to produce a noise-reduced image. A blending operation is performed on luminance image of the noise-reduced image and luminance image of the second image in YCbCr format, and thereafter a chrominance image is combined with the blended image to produce a processed image. A noise reducing degree of the noise-reduced image is higher than that of the second image in YCbCr format.

Abstract: A face recognition system and a face recognition method thereof. The face recognition system comprises a storage module, a processing module and a display module. The storage module stores a plurality of face recognition codes, a plurality of face images or face coordinates corresponding to the plurality of face recognition codes. The processing module calculates an overlap rate of the (T?1)th face image that overlaps the Tth face image in the plurality of face images. When the overlap rate is greater than a first preset value, the processing module calculates a similarity between the (T?1)th face image and the Tth face image. If the similarity is smaller than a second preset value, the processing module retains the face recognition code of the (T?1)th face image. The display module displays the face recognition code in the Tth face image.

Abstract: An auto focus (AF) method and an AF apparatus are provided. The method includes the following steps. At least one target object is selected and photographed by a first image sensor and a second image sensor to generate a three-dimensional (3D) depth map. A block covering at least one initial focusing point is selected. The 3D depth map is queried for reading depth information of a plurality of pixels in the block. It is determined whether depth information of the pixels is enough to operate. If yes, a first statistics operation is performed, and focusing depth information is obtained. If not, the position of the block is moved or the size of the block is enlarged to obtain the focusing depth information. A focusing position is obtained according to the focusing depth information and the AF apparatus is driven to perform an AF procedure according to the focusing position.

Abstract: An auto focus (AF) method adapted to an AF apparatus is provided. The AF method includes following steps. A target object is selected and photographed by a first image sensor and a second image sensor to generate a first image and a second image. A procedure of three-dimensional (3D) depth estimation is performed according to the first image and the second image to generate a 3D depth map. An optimization process is performed on the 3D depth map to generate an optimized 3D depth map. A piece of depth information corresponding to the target object is determined according to the optimized 3D depth map, and a focusing position regarding the target object is obtained according to the pieces of depth information. The AF apparatus is driven to execute an AF procedure according to the focusing position. Additionally, an AF apparatus is provided.

Abstract: An image processing method is provided and includes the following steps. A source image arranged in a Bayer pattern is captured. A first-order image process is performed on the source image to produce a first image in YCbCr format. A second-order image process is performed on the source image to produce a second image in YCbCr format. Then, a noise-reducing process is performed on the first image in YCbCr format to produce a noise-reduced image. A blending operation is performed on luminance image of the noise-reduced image and luminance image of the second image in YCbCr format, and thereafter a chrominance image is combined with the blended image to produce a processed image. A noise reducing degree of the noise-reduced image is higher than that of the second image in YCbCr format.

Abstract: An image capturing device and an image processing method are provided. The present method includes following steps. A first image and a second image are captured with a first focal length and a second focal length correspondingly. The motion corrected second image is produced by performing geometric correction procedure on the second image. A gradient operation is performed on each of the pixels of the first image to obtain a plurality of first gradients, and the gradient operation is performed on each of the pixels of the motion corrected second image to obtain a plurality of second gradients. The first gradients and the second gradients are compared and a first parameter map is generated according to the comparison results. A blending image is produced in according with the first parameter map and the first image, and an output image is produced at least in according with the blending image.

Abstract: An entered image is divided into a plurality of windows and it is determined, on a per-window basis, whether the image data within an applicable window is indicative of the color white, based upon the position of each window in the image and the continuity to its surrounding divided windows. A white balance method is performed based upon data of a window determined to be indicative of the color white. The present invention conducts a white balance process through the addition of determining the light source type weight and calculating the continuity of each divided window and its surrounding divided windows. In order the white balance process to accurately obtain the colors of an entered image even under the conditions of specific scenes with distinctive colors.

Abstract: A method of detecting the subject of an image and imaging device thereof are disclosed. The method comprises the following steps of providing an image capturing module to capture the temporal image, providing the image processing module to receive the temporal image and to determine a plurality of objects from the temporal image, using the image processing module to define a plurality of regions on the temporal image based on the center of temporal image, using the image processing module to assign an initial setup value to each of the objects according to the region corresponding to each of the objects, using the imaging processing module to execute an operation to increase or decrease each of the initial setup values, using the image processing module to execute a sorting, and selecting at least one of the objects as a subject of the temporal image.

Abstract: An image processing method and an apparatus using the same are provided. The method includes the following steps: deriving a global motion vector between a first image and a second image and providing the first image, the second image and the global motion vector to a first application process, wherein the first image is the previous image of the second image; deriving a first compensated image and a second compensated image by performing a lens distortion compensation process on the first image and the second image respectively; deriving a compensated global motion vector corresponding to the first compensated image and the second compensated image by transforming and correcting the global motion vector; and providing the first compensated image, the second compensated image, and the compensated global motion vector to a second application process.