Altek Corporation

Industrial Technology Research Institute

Altek Semiconductor Corp.

Altek Autotronics Corporation

Ming-Jiun Liaw

Hong-Long Chou

Yuh-Ren Shen

Yu-Chih Wang

Chien-Chih Chen

Shih-Yuan Peng

Ching-Lung Tsai

Ho-Hsin Yang

Simon Mong-Lun Law

Ming-Daw Chen

Yuhren Shen

Che-Lun Chuang

Chan-Min Chou

Chen-Hung Chan

Yu-Chen Huang

Yen-Ping Teng

Yong-Nien Rao

Yi-Yi Yu

Chien-Hsiang Lin

Cheng-Chih Hsu

I-Te Yu

Ching-Sung Yeh

Chao-Yi Lin

Chi-Fang Hsieh

A method for generating an orientation image, adapted to an electronic device, includes the following steps. A plurality of input pixels including a current input pixel of an input image is received. Edge detection is performed on the current input pixel in a first and second direction to generate a first current gradient and a second current gradient respectively with respect to the first direction and the second direction. A ratio of the first current gradient to a current gradient absolute sum is calculated to obtain a current ratio, where the current gradient absolute sum is a sum of absolute values of the first and second current gradient. A sign of the second current gradient is extracted to obtain a current sign. The current ratio and the current sign are inputted to a lookup table to obtain an image orientation angle corresponding to the current input pixel.

Method for generating orientation image

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.

Image capturing device and method for calibrating image deformation thereof

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.

Image capturing device and method for calibrating image defection thereof

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.

An object detection system including a storage unit, image acquisition module, feature searching module, calculation module, and confirmation module is provided. The image acquisition module obtains a first, second, and third image respectively corresponding to a first, second, and third timepoint of a video sequence from the storage unit, where time difference between the first and second timepoint is less than or equal to that between the second and third timepoint. The feature searching module searches for at least one feature from the first image. When the feature is within a near-distance detected region, the calculation module calculates a motion vector of the feature according to the first and second image; otherwise, it calculates the motion vector of the feature according to the third and one of the first and second image. The confirmation module confirms the existence of a moving object according to the motion vector of the feature.

Object detection system

An obstacle detection device is provided, which includes a storage unit, a quasi-vertical edge detection module, an intersection determination module, a position determination module, and an obstacle detection module. The quasi-vertical edge detection module receives an input image and performs a quasi-vertical edge detection procedure on the input image to obtain a plurality of quasi-vertical edges. The intersection determination module determines whether the quasi-vertical edges intersect a predetermined virtual horizontal. If one of the quasi-vertical edges intersects the predetermined virtual horizontal, the position determination module determines whether an end of one of the quasi-vertical edges intersecting the predetermined virtual horizontal is located in a detection zone. If one end of one of the quasi-vertical edges intersecting the predetermined virtual horizontal is located in the detection zone, the obstacle detection module determines that an obstacle exists and issues a warning.

Obstacle detection device

The invention provides a flash light device, which includes a light source, a light diffuser and a light diffuser's driving unit. The light diffuser's driving unit provides the light diffuser with a required driving voltage according to a voltage information, in which the voltage information is determined according to an original image without light-complementing of the light source and a pre-flash image with light-complementing of the light source.

Flash light device

An auto-focus (AF) method adapted for an image capturing device includes following steps. When a first press signal generated by a user pressing a button of the image capturing device is detected, a local peak searching method is applied to perform an AF procedure. It is determined whether a second press signal generated by the user pressing the button is detected. If not, it is determined whether a first released signal generated by the user releasing the button is detected. The continuous pressing count is calculated according to the first released signal and the first press signal that are continuously generated. Whether the continuous pressing count is greater than a first threshold is determined. If yes, a global peak searching method is applied to perform the AF procedure. If not, the local peak searching method is still applied to perform the AF procedure.

Auto-focus method

A voltage-controlled light diffusing module, a flash lamp module and a controlling method thereof are provided. The voltage-controlled light diffusing module includes a light diffuser, a driving circuit and an information processing unit. The information processing unit receives face information for deciding a driving voltage of the driving circuit, so as to change transmission of the light diffuser.

Voltage-controlled light diffusing module, flash lamp module and controlling method thereof based on face information

An automatic focusing method and device in a high-noise environment are used for determining a focusing distance between a digital imaging device and an object to be photographed. The automatic focusing method includes the steps of capturing M pre-photographed images at different object distances respectively; loading the pre-photographed images; superposing every N (N&#x3c;M) pre-photographed images to create (M&#x2212;N+1) composite images; redefining the object distances corresponding to the (M&#x2212;N+1) composite images; calculating high-frequency signals in the focusing regions of the (M&#x2212;N+1) composite images; determining an optimum focusing object distance based on the relation between the high-frequency signals and corresponding object distances; and adjusting an automatic focusing lens to the optimum focusing object distance and accomplishing focusing.

Automatic focusing method and device in high-noise environment

A color interpolation method for a digital image is described, includes the following steps. Edge information is generated according to the Bayer pattern. A Bayer pattern image is processed by a horizontal band-pass filter and a vertical band-pass filter to generate a horizontal edge signal and a vertical edge signal. A weight process implements a weight adjustment on the horizontal edge signal and the vertical edge signal to generate a luminance signal and outputs the luminance signal to a subtraction unit. The subtraction unit carries out an operation according to the Bayer pattern image and an output result of the weight process to generate a chrominance pattern. The chrominance pattern is compensated through a chrominance interpolation process, so as to generate image signal patterns of different colors. The image signal patterns of different colors are output to an adder for an add operation, thereby outputting a complete color image.

Color interpolation method for digital image

A tone adjustment method for a digital image and an electronic apparatus using the same are presented. A digital image is loaded. A detail image layer and a primary image layer are generated according to the digital image. A tone mapping procedure is performed on the primary image layer, for generating a tone mapping layer. A detail gain lookup table is loaded and then a corresponding gain is looked up according to each pixel value in the primary image layer, for generating a detail gain adjustment layer. A detail gain control procedure is performed and then a detail gain adjustment is performed on the detail gain adjustment layer and the detail image layer, for generating a gain correction layer. The gain correction layer and the tone mapping layer are combined, and then a combined layer is output, thereby completing the tone adjustment for the digital image.

Tone adjustment method for digital image and electronic apparatus using the same

An automatic focusing method in a high-noise environment and a digital imaging device using the same are used for determining an object distance. The method includes taking two digital images at a farthest object distance and taking two digital images at a nearest object distance, under a first exposure condition and a second exposure condition; capturing digital images under the first exposure condition at a plurality of different object distances other than the farthest and nearest object distances; selecting at least two images captured at adjacent object distances to create a composite image; calculating an object distance of the composite image; calculating high-frequency signals of the second farthest object distance image, the second nearest object distance image, and the composite image in the focusing frame; determining from the images an object distance corresponding to the maximum high-frequency signal; and moving an automatic focusing lens to the object distance.

Automatic focusing method in high-noise environment and digital imaging device using the same

A method for an image adjustment is disclosed. The method comprises the steps of: reading an interested pixel and its plural neighboring pixels from an image storage device; determining a so-called first gradient value of the first direction and a so-called second gradient value of the second direction, wherein the first direction is the orthogonal direction of the second direction; comparing the first and the second gradient values; executing a sharpness adjustment to the interested pixel along the direction which has larger gradient value; then executing a noise reduction or smoothing adjustment to the interested pixel along the direction which has smaller gradient value; and repeating the steps until all interested pixels are processed and obtaining a new pixel value.

Method for an image adjustment

A LCD driving system for increasing LCD response times. Voltages across liquid crystals are increased by modulating gamma reference voltages fed to a data driver, modulating image codes fed to the data driver, or both. Particularly, around the highest and the lowest image code, modulation of gamma reference voltages fed to a data driver is most effective.

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Miaoli County, Taiwan

Ming-Jiun Liaw