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: An apparatus capable of detecting location of object contained in image data and its detecting method are disclosed. The apparatus comprises an image capturing module, a weight assignment module, and a processing module. The image capturing module is for capturing an image. The weight assignment module performs the pixel weight/probability assignment according to the priori information and the image, and figures out the initial gravity center of the object according to the object location initialization. The processing module performs the statistical analysis according to the result of the pixel weight/probability assignment and the initial gravity center of the object so as to obtain the analysis result and update the object location. The processing module determines whether or not the analysis result meets the preset value, if it does, the processing module outputs an estimated result; if it doesn't, the processing module repeats the foregoing processes.

Abstract: This invention discloses an image capturing device, an image capturing method, and a human recognition photograph system. The image capturing device comprises: a capturing module sensing an image; a human detecting module detecting the number of at least one person in an image generating detecting signal; a face recognition module generates recognition signal by recognizing a face condition of the at least one person in the image; and a processing module that receives detecting signal and recognition signal and calculates the number of at least one person and face condition value according to the detecting signal and the recognition signal respectively. The processing module determines whether the number of at least one person and face condition value correspond to a predetermined number and a predetermined face condition value respectively; if so, generating an image capturing signal to control the capturing module to capture image and generate image data.

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: A license plate image-pickup device and an image white balance adjustment method thereof applicable to vehicles. The license plate image-pickup device comprises an image-sensing module, a recognition module, a data base and a processing module. The image-sensing module senses a scene to produce an image. The recognition module recognizes an object contained in the image and a license plate color feature contained in the object to produce recognition parameter set. The database saves parameter sets of reference objects and reference license plate color features respectively corresponding to the reference objects. The processing module searches the reference objects in the database according to the recognition parameter set, to obtain a corresponding reference license plate color feature, and adjusting the white balance of the image according to the corresponding reference license plate color feature.

Abstract: An object tracking method includes steps of obtaining multiple first classifications of pixels within a first focus frame in a first frame picture, wherein the first focus frame includes an object to be tracked and has a first rectangular frame in a second frame picture; performing a positioning process to obtain a second rectangular frame; and obtaining color features of pixels around the second rectangular frame sequentially and establishing multiple second classifications according to the color feature. The established second classifications are compared with the first classifications sequentially to obtain an approximation value, compared with a predetermined threshold. The second rectangular frame is progressively adjusted, so as to establish a second focus frame. By analyzing color features of the pixels of the object and with a classification manner, the efficacy of detecting a shape and size of the object so as to update information of the focus frame is achieved.

Abstract: A device and a method for predicting photograph timing. First, a detection step is performed. Then, a face determination step is performed to determine whether or not a face is shown. A face-classifying step is then performed. If a detected image is a non-front face, a difference generation step is then performed. A difference determination step is performed when a plurality of differences are obtained to determine whether or not the sequentially adjoined differences are reduced, wherein if the sequentially adjoined differences are reduced, a photographing timing is predicted according to a reduction degree of the differences. As a result, the probability of successfully photographing the front face can be enhanced. In addition, a training database that has both front face information and non-front face information can be utilized. As a result, it is not easy to determine the non-front face as the front face incorrectly.

Abstract: A vehicle apparatus control system and method thereof are disclosed. The vehicle apparatus control system comprises a data storage module, an image capturing module, a face recognition module and a control module. The data storage module stores multiple registered users' facial feature parameters and vehicle apparatus setting parameters, and integration setting data. The face recognition module detects several facial images contained in the captured image and recognizes the users corresponding to the face images according to the facial feature parameters stored in data storage module. The control module set a vehicle apparatus according to the integration setting data, and the corresponding users' vehicle apparatus setting parameters.

Abstract: A feature data compression device, a multi-directional face detection system and a detection method thereof. The feature data compression device comprises a mirror unit and a transposition unit. The mirror unit compares and computes a plurality of feature values each other to obtain a position of each mutual symmetric feature value and abandoning one of each two symmetric feature values to form first mirrored data, or to obtain a position of the feature value with the highest weight value to form second mirrored data. The transposition unit transposes at least one image template with an angle based on a transposition table for obtaining transposed data.

Abstract: A feature data compression device, a multi-directional face detection system and a detection method thereof. The feature data compression device comprises a mirror unit and a transposition unit. The mirror unit compares and computes a plurality of feature values each other to obtain a position of each mutual symmetric feature value and abandoning one of each two symmetric feature values to form first mirrored data, or to obtain a position of the feature value with the highest weight value to form second mirrored data. The transposition unit transposes at least one image template with an angle based on a transposition table for obtaining transposed data.

Abstract: An apparatus capable of detecting location of object contained in image data and its detecting method are disclosed. The apparatus comprises an image capturing module, a weight assignment module, and a processing module. The image capturing module is for capturing an image. The weight assignment module performs the pixel weight/probability assignment according to the priori information and the image, and figures out the initial gravity center of the object according to the object location initialization. The processing module performs the statistical analysis according to the result of the pixel weight/probability assignment and the initial gravity center of the object so as to obtain the analysis result and update the object location. The processing module determines whether or not the analysis result meets the preset value, if it does, the processing module outputs an estimated result; if it doesn't, the processing module repeats the foregoing processes.

Abstract: An automobile equipment control system and a control method thereof. The system comprises an input module, a storage module, an image capturing module, a first recognizing module, a second recognizing module and a processing module. The input module is used to input a plurality of vehicle equipment setting values. The storage module is used to save a plurality of facial characteristic values and a plurality of setting values of vehicle equipment. The image capturing module is used to capture the image of the user. The first recognizing module analyzes the facial image in the image and extracts a facial characteristic point from the facial image. The second recognizing module analyzes the user's hand gesture, the user's head gestures or what the user speaks so as to decide which setting value of vehicle equipment is adopted to control the vehicle equipment.

Abstract: A device and a method for predicting photograph timing. First, a detection step is performed. Then, a face determination step is performed to determine whether or not a face is shown. A face-classifying step is then performed. If a detected image is a non-front face, a difference generation step is then performed. A difference determination step is performed when a plurality of differences are obtained to determine whether or not the sequentially adjoined differences are reduced, wherein if the sequentially adjoined differences are reduced, a photographing timing is predicted according to a reduction degree of the differences. As a result, the probability of successfully photographing the front face can be enhanced. In addition, a training database that has both front face information and non-front face information can be utilized. As a result, it is not easy to determine the non-front face as the front face incorrectly.

Abstract: A vehicle apparatus control system is used to control at least one piece of vehicle equipment in a vehicle, and includes a data storage module, an image capture module, a face recognition module, and a control module. The data storage module stores a plurality of facial expression parameters therein. The face recognition module detects a face image from an image captured by the image capture module and determines a facial expression in the face image based on the facial expression parameters. The control module controls the vehicle equipment to enter into a first state based on the facial expression. When the facial expression is recognized as a sleeping facial expression, the control module controls the vehicle seat to move into a horizontal position and mutes a vehicle stereo. A vehicle apparatus control method for controlling at least one piece of vehicle equipment in a vehicle is also disclosed.

Abstract: A vehicle apparatus control system and method thereof are disclosed. The vehicle apparatus control system comprises a data storage module, an image capturing module, a face recognition module and a control module. The data storage module stores multiple registered users' facial feature parameters and vehicle apparatus setting parameters, and integration setting data. The face recognition module detects several facial images contained in the captured image and recognizes the users corresponding to the face images according to the facial feature parameters stored in data storage module. The control module set a vehicle apparatus according to the integration setting data, and the corresponding users' vehicle apparatus setting parameters.

Abstract: A television system with face recognition, a multimedia reproducing system and a reproducing system control method thereof are disclosed. The multimedia reproducing system comprises a multimedia module, a storage module, an image capture module and a face recognition module. The storage module stores a user's facial feature parameter and watch rate. The face recognition module detects a face image from an image captured by the image capture module, and recognizes the user corresponding to the face image according to the facial feature parameters stored in the storage module. The multimedia module filters the multimedia contents according to the corresponding user's watch rate.

Abstract: An object tracking method includes steps of obtaining multiple first classifications of pixels within a first focus frame in a first frame picture, wherein the first focus frame includes an object to be tracked and has a first rectangular frame in a second frame picture; performing a positioning process to obtain a second rectangular frame; and obtaining color features of pixels around the second rectangular frame sequentially and establishing multiple second classifications according to the color feature. The established second classifications are compared with the first classifications sequentially to obtain an approximation value, compared with a predetermined threshold. The second rectangular frame is progressively adjusted, so as to establish a second focus frame. By analyzing color features of the pixels of the object and with a classification manner, the efficacy of detecting a shape and size of the object so as to update information of the focus frame is achieved.