Abstract: A system and method for reducing the risk of road accidents on account of blind spot errors and a vehicle using the system and method includes a visual sensing unit, the visual sensing unit comprising a first camera and a second camera, wherein the first camera looks left and obtains a first image information, the second camera looks to the right and obtains a second image information; a pre-processing unit, the pre-processing unit being coupled with the visual sensing unit, wherein the pre-processing unit processes the first image information and the second image information to generate a single image. An image processing unit generates an obstacle recognition information according to the processed image.

Abstract: A parachute device for drone includes a container, a power source, a base, a parachute body and an open-assist member. A top of the container has an opening. The power source is disposed on a bottom of the container. The base is disposed on the power source. The parachute body, disposed on the base, is in a folded status. The open-assist member is disposed in the parachute body. The open-assist member contacts the base and the center of the inner surface of the parachute body.

Abstract: A parachute device for drone includes a container, a power source, a base, a parachute body and an open-assist member. A top of the container has an opening. The power source is disposed on a bottom of the container. The base is disposed on the power source. The parachute body, disposed on the base, is in a folded status. The open-assist member is disposed in the parachute body. The open-assist member contacts the base and the center of the inner surface of the parachute body.

Abstract: A target object identification method includes acquiring an image to be identified, identifying at least one target area in the image and marking the target area to obtain at least one marked area, performing binarization processing on the marked area, identifying the boundary pixels and effective pixels of the target area in the marked area, and determining a center and a size of the target area according to a position of the boundary pixels and the effective pixels. An area of the marked area is greater than or equal to an area of the target area. The target area is located within the marked area. A color of pixels of the target area after the binarization process is different from a color of pixels outside the target area.

Abstract: A target object identification method includes acquiring an image to be identified, identifying at least one target area in the image and marking the target area to obtain at least one marked area, performing binarization processing on the marked area, identifying the boundary pixels and effective pixels of the target area in the marked area, and determining a center and a size of the target area according to a position of the boundary pixels and the effective pixels. An area of the marked area is greater than or equal to an area of the target area. The target area is located within the marked area. A color of pixels of the target area after the binarization process is different from a color of pixels outside the target area.

Abstract: A navigation method comprising: scanning two-dimensional codes using a code scanning unit of a user terminal and obtaining two-dimensional code; comparing the information of the acquired two-dimensional code with the information in a database, and marking the position corresponding to each two-dimensional code in a map, wherein the database stores the map of the preset area and a relation of all positions of the map and the two-dimensional code information; receiving a target position input by a user, and finding a path information between the current position corresponding to the two-dimensional code and the target position; and outputting the current position and the path information.

Abstract: A method for monitoring an object is provided. The method includes acquiring videos recorded by an imaging device of a vehicle and position of the vehicle, and storing the videos and the position into a database, and receiving a monitoring command from a terminal device, wherein the monitoring command comprising a dynamic monitoring command and/or a static monitoring command. The method further can obtain a search result by searching in the database according to the monitoring command and/or the static monitoring command and output the search result.

Abstract: A system suspending method, a system resuming method and a computer system using the same are provided. The system resuming method of the computer system is applied for resuming the computer system to be a normal status (S0 status) from a suspend-to-ram status (S3 status) or a suspend-to-disk status (S4 status). The computer system includes a plurality of peripheral devices and a central processing unit. The peripheral devices are classified into a first group and a second group. The system resuming method includes the following steps. The central processing unit is powered on. Then, the peripheral devices belonging in the first group are resumed. Next, the computer system is thawed.

Abstract: A method for initializing a peripheral device and an electronic device using the method. The electronic device includes one or more peripheral devices having registers, a memory having a data storing module, and an instruction capturing module. The instruction capturing module captures a plurality of hardware register settings from a driver execution process of the one or more peripheral devices, stores the plurality of hardware register settings in the data storing module, and serializes or concatenates the plurality of hardware register settings to form serialized hardware register settings, when the electronic device is performing a non-hibernation resume or non-wakeup cold boot to execute an initialization process of the one or more peripheral devices. The one or more peripheral devices are initialized by the serialized hardware register settings, when the electronic device is performing cold boot again due to a hibernation resume or wakeup to execute the initialization process.

Abstract: A system suspending method, a system resuming method and a computer system using the same are provided. The system resuming method of the computer system is applied for resuming the computer system to be a normal status (S0 status) from a suspend-to-ram status (S3 status) or a suspend-to-disk status (S4 status). The computer system includes a plurality of peripheral devices and a central processing unit. The peripheral devices are classified into a first group and a second group. The system resuming method includes the following steps. The central processing unit is powered on. Then, the peripheral devices belonging in the first group are resumed. Next, the computer system is thawed.

Abstract: An electronic apparatus and a method for resuming from hibernation are disclosed. The electronic apparatus comprises an external storage, a main memory, an image generating circuit and a page moving circuit. The image generating circuit writes pages from the main memory into the external storage to generate a hibernation image file during a hibernation process. The page moving circuit according to the hibernation image file sequentially writes the pages from the external storage back to a continuous page range of the main memory during a resume process. The resume process is later than the hibernation process.

Abstract: A white balance adjustment method includes capturing a raw image by an image capturing device where an arrangement format of the raw image is BGb/GrR, a predetermined sampling width is used to sample RGB pixels, and obtaining color scale values of each channel. Each channel includes a first buffer space and a second buffer space, the first buffer space storing smaller color scale values, the second buffer storing larger color scale values, an average value of the minimum color scale values stored in the first buffer space is calculated to obtain a reference black, an average value of the maximum color scale values stored in the second buffer space is calculated to obtain a reference white. A color histogram stretching method using the obtained reference black and white adjusts the white balance of the raw image.

Abstract: A white balance adjustment method includes capturing a raw image by an image capturing device where an arrangement format of the raw image is BGb/GrR, color scale values of each color channel are extracted, the color scale values of all pixels in B, Gb, Gr, and R channels are separately scanned, and predetermined number ranges are used to classify the color scale values, then obtaining a cumulative proportion of color scale values in each channel is obtained. The cumulative proportions of each channel are compared with default minimum and maximum values, to obtain a more-than-maximum as a reference white, and a less-than-minimum as a reference black. The color scale values are re-quantized, according to the reference white and black, and a color histogram stretching method is applied to complete the white balance adjustment.

Abstract: An electronic apparatus and a method for resuming from hibernation are disclosed. The electronic apparatus comprises an external storage, a main memory, an image generating circuit and a page moving circuit. The image generating circuit writes pages from the main memory into the external storage to generate a hibernation image file during a hibernation process. The page moving circuit according to the hibernation image file sequentially writes the pages from the external storage back to a continuous page range of the main memory during a resume process. The resume process is later than the hibernation process.

Abstract: Method for generating a reduced snapshot image for booting and a computing apparatus are provided. An embodiment of the method includes the following. In response to a shutdown request, it is determined whether a specific boot mode is enabled. When the specific boot mode is enabled, a threshold parameter set for process killing is assigned. If a first memory unit of the computing apparatus has at least one process satisfying a process killing condition, the at least one process satisfying the process killing condition is killed. The process killing condition includes a criterion based on the threshold parameter set. A hibernation process is entered, wherein the hibernation process generates a snapshot image for booting and stores the snapshot image in a second memory unit of the computing apparatus and the snapshot image includes at least one process reserved in the first memory after the killing step.

Abstract: A white balance adjustment method includes capturing a raw image where an arrangement format of the raw image is BGb/GrR, extracting color scale values of each color channels, and obtaining cumulative proportion of color scale values in each channel. Cumulative proportion of each channels are compared with default minimum and maximum values, to get a cumulative proportion which is above a maximum value treated as a reference white, and a cumulative proportion below the minimum value treated as a reference black. The color scale values are re-quantized according to the obtained reference white and black, by using a color histogram equalization method.

Abstract: A white balance adjustment method includes capturing a raw image by an image capturing device, setting an initial maximum and an initial minimum threshold values of each channels, and obtaining a reference white and a reference black. Color scale values of each R, G, and B channels are extracted and a minimum, a maximum, and an average values of the color scale values corresponding to each channels are obtained. A modulation factor of each channel is defined by using above defined three values, according to the modulation factor of each channels to re-define a new maximum threshold value as a reference white and a new minimum threshold value as a reference black. According to the obtained reference black and the reference white to complete the white balance adjustment of the image.

Abstract: An auto-focus method to determine an optimum position of a lens module includes defining search boundaries and an allowable difference, randomly sampling current values within the search boundaries d1, d2 and d3, and obtaining sharpness m1, m2 and m3. A parabola is determined where a vertex of the parabola is used as a next input current value where three larger values of the sharpness are used along with corresponding current values to re-determine a new parabola. Three current values are sampled and a corresponding current value is used to re-determine a new parabola and according to a comparison of the sharpness values, the lens module is driven to auto-focus.

Abstract: A focus position searching method is used to determine an optimum position of a lens module, the lens module being driven by a voice coil motor (VCM), the VCM according to an input current to drive the lens module. The focus position searching method is used to search a left boundary and a right boundary, then two current values are obtained in a range between the left and the right boundaries, by using a golden section method to drive the lens module to capture an image and calculate sharpness of the image. According to the sharpness, the left and the right boundaries are continuously moved rightward and leftward, thereby two differences current values are obtained in the left and right boundaries within a certain range, and a searched current is used to carry out the focus.

Abstract: An auto focus method includes: assigning searching boundaries L=InitL, R=InitR, and acquiring the resolutions f(L), f(R); defining the focused positions X1, X2 by the golden section method, and acquiring the resolution f(X1), f(X2); determining whether or not f(X1) is greater than f(X2); moving L adjacent to R when f(x1) is less than f(x2); moving R adjacent to L when f(x1) is greater than f(x2); acquiring the focused positions L, x1, x2, and R, and the resolution of the focused positions when L?InitL and R?InitR; acquiring an optimal focus point according to the focused positions L, X1, X2, and R, and the resolution of the focused positions.