KR102112784B1 - Apparatus and method for correcting distored image - Google Patents

Abstract

The present invention relates to distortion image correction, in particular, by optimizing the nonlinear region of the image taken through the fisheye lens to generate a corrected image, it is possible to minimize the difference between the image taken through the fisheye lens and the actual shooting object. It relates to a distortion image correction apparatus and method capable of providing a more realistic image.
For this, in the distortion image correction apparatus according to an embodiment of the present invention, when an image photographed from one or more cameras is input, an image pre-processing unit that adjusts a long and short ratio of the input image is applied, and an image adjusted through the image pre-processing unit is applied. When there is, it may be configured to include a parameter calculating unit for calculating a camera parameter for optimizing the nonlinear region of the adjusted image and a corrected image generating unit for generating a corrected image using the calculated camera parameter from the adjusted image.

Description

Distortion image correction apparatus and method {APPARATUS AND METHOD FOR CORRECTING DISTORED IMAGE}

The present invention relates to distortion image correction, in particular, by optimizing the nonlinear region of the image taken through the fisheye lens to generate a corrected image, it is possible to minimize the difference between the image taken through the fisheye lens and the actual shooting object. It relates to a distortion image correction apparatus and method capable of providing a more realistic image.

The contents described in this section merely provide background information for this embodiment, and do not constitute a prior art.

In general, a fisheye lens may be included in a camera installed at the rear of a vehicle or a video surveillance camera to assist in parking, and may be used to photograph surrounding images. Such a fisheye lens can acquire an area of 180 degrees or more, thereby ensuring a maximum viewing angle with a minimum camera, and intentionally creating a distortion of a barrel to maintain uniform brightness and sharpness over the entire view angle of 180 degrees or more. Can be configured to. Accordingly, it is possible to acquire a wide area image through a fish-eye lens.

However, in the fish-eye lens, the subject caught in the center of the lens is photographed extremely large, and the surrounding background is photographed very small. Therefore, the image photographed through the fish-eye lens has severe distortion, and thus a difference from the actual photographing object is generated, thereby deteriorating the sense of reality.

Accordingly, various techniques have been developed to correct distortion of an image photographed through such a fish-eye lens, but so far, there is no technique capable of optimizing and correcting a non-linear portion present in an image such as a corner portion of the image.

The present invention is proposed to solve the conventional discomfort, and by optimizing the nonlinear region of the image taken through the fisheye lens to generate a corrected image, minimizing the difference between the image taken through the fisheye lens and the actual shooting object An object of the present invention is to provide an apparatus and method for correcting distorted images.

To this end, the present invention can reduce the time required for calculation by dividing the calculation process of a camera parameter capable of optimizing the nonlinear region of the captured image, and organically adjust the distortion correction ratio calculated using the camera parameter. It is an object of the present invention to provide a distortion image correction apparatus and method capable of generating a more accurate correction image by applying it to an image.

Distorted image correction apparatus according to a preferred embodiment of the present invention for solving the above-described problems, when an image photographed from one or more cameras is input, an image pre-processing unit for adjusting the long and short axis ratio of the input image; A parameter calculator configured to calculate a camera parameter for optimizing a nonlinear region of the adjusted image when the adjusted image is applied through the image preprocessing unit; And a corrected image generator that generates a corrected image using the calculated camera parameters from the adjusted image.

At this time, after extracting the feature points of the input image, the image pre-processing unit checks the long and short lengths of the region to which the feature points are connected, calculates a scaling factor using the long and short lengths, and applies them to the input image and inputs them. You can adjust the long and short video ratio.

In addition, the parameter calculator may calculate camera parameters so that a value of a predefined function is minimized by using feature points calculated through the image preprocessor.

At this time, the camera parameters include an internal parameter including any one of parameters for a focal length, a field of view, and a skew vector of a lens provided in the camera and the camera. It may be configured to include an external parameter including any one of the rotation and movement parameters.

In addition, the parameter calculating unit may calculate the internal parameter, and calculate an external parameter using the calculated internal parameter and feature points calculated through the image preprocessing unit.

In addition, the corrected image generation unit generates a corrected image by calculating a distortion correction ratio using the camera parameter calculated through the parameter calculation unit in the adjusted image, but is distorted according to the distance from the center point based on the adjusted image center point. A correction image may be generated by adjusting a correction ratio.

A method of correcting a distorted image according to a preferred embodiment of the present invention for solving the above-described problem may include adjusting a long axis and a shortened ratio of the input image when an image captured from one or more cameras is input; Calculating camera parameters for optimizing the nonlinear region of the adjusted image; And generating a corrected image using the camera parameter from the adjusted image.

Here, adjusting the long axis and short axis ratio may include extracting feature points of the input image; Calculating a ratio of a long axis and a short axis length of the region connecting the extracted feature points; Calculating a scaling factor based on the ratio of the long axis and the short axis length; And adjusting the long and short axis ratios of the input image by applying the scaling factor to the input image.

In addition, in the calculating of the camera parameters, the camera parameters may be calculated to minimize the value of a predefined function using the extracted feature points.

In addition, generating the corrected image may include calculating a distortion correction ratio using the camera parameter; And adjusting the distortion correction ratio according to the distance from the center point based on the center point of the adjusted image to generate a corrected image.

In addition, the present invention can further provide a computer-readable recording medium, characterized in that a program for executing the above-described distortion image correction method is recorded.

According to the distortion image correction apparatus and method of the present invention, the ratio of the long and short axis lengths of an image photographed through a fish-eye lens of a camera is matched, a parameter value for the camera is calculated, and the ratio is calculated using the calculated parameter value. By optimizing the nonlinear region of the matched image to generate a corrected image, it is possible to secure a maximum viewing angle by using a wide viewing angle of a fish-eye lens.

Due to this, it is possible to provide a realistic image by minimizing the difference between the image taken using the fisheye lens and the actual shooting object, and it is possible to secure the maximum viewing angle with the smallest camera in the parking assist system to which it is applied, There is an effect that can provide more accurate information to the user.

1 is a view showing the configuration of an image processing system according to an embodiment of the present invention.
2 is a view showing the configuration of a distortion image correction apparatus according to an embodiment of the present invention.
3 is an exemplary diagram for describing an FOV model according to an embodiment of the present invention.
4 is an exemplary diagram for explaining a process of adjusting a long axis and a short axis ratio of an input image according to an embodiment of the present invention.
5 is an exemplary view for explaining a real-world coordinate system and a camera coordinate system according to an embodiment of the present invention.
6 is a flowchart for explaining a process of calculating camera parameters composed of steps 1 and 2 according to an embodiment of the present invention.
7 is a flowchart illustrating a distortion image correction method according to an embodiment of the present invention.
8 and 9 are exemplary views of an input image and a corrected image according to an embodiment of the present invention.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. However, in the following description and accompanying drawings, detailed descriptions of well-known functions or configurations that may obscure the subject matter of the present invention are omitted. In addition, it should be noted that the same components throughout the drawings are denoted by the same reference numerals as much as possible.

The terms or words used in the present specification and claims described below should not be construed as being limited to ordinary or dictionary meanings, and the inventor is appropriate as a concept of terms for explaining his or her invention in the best way. Based on the principle that it can be defined, it should be interpreted as meanings and concepts consistent with the technical spirit of the present invention. Therefore, the configuration shown in the embodiments and drawings described in this specification is only one of the most preferred embodiments of the present invention, and does not represent all of the technical spirit of the present invention, and can replace them at the time of this application. It should be understood that there may be equivalents and variations.

First, an image processing system according to an embodiment of the present invention will be described in detail with reference to the accompanying drawings.

1 is a view showing the configuration of an image processing system according to an embodiment of the present invention.

Referring to FIG. 1, an image processing system may include one or more cameras 100, a distortion image correction device 200, and an image output device 300.

The one or more cameras 100 are devices capable of acquiring a wide area image, and may preferably include a fish eye lens, which is an ultra wide-angle lens having an angle of view of 180 ° or more. The camera 100 including the fisheye lens may be installed at the rear of the vehicle to support parking of the vehicle, and may provide an image of a rear of the vehicle and a blind spot image to a driver driving toward the front.

At this time, the camera 100 including a fish-eye lens acquires a 3D image as a 2D image, where the acquired image has severe distortion, for example, the distortion is expanded radially based on the lens center point or There may be a reduction in radial distortion.

An example of such radiation distortion is illustrated in FIG. 8, and as illustrated in FIG. 8, subjects at the lens center point are taken extremely large, and surrounding subjects are taken at a very small size compared to the object at the lens center point.

When the image captured by the one or more cameras 100 is input, the distortion image correction apparatus 200 corrects the input image to generate a correction image. In particular, the distortion image correcting apparatus 200 of the present invention adjusts the long and short axis ratios of the input image, calculates camera parameters for optimizing the nonlinear region of the adjusted image, and then generates a corrected image using the same.

At this time, when generating a corrected image, the image can be corrected by adjusting the distortion correction ratio. In order to enable the user to recognize the image without losing the maximum viewing angle, the distortion correction ratio is adjusted according to the distance from the center point based on the center point of the image. By differently, a corrected image can be generated.

The distortion image correcting apparatus 200, for example, secures a maximum viewing angle with a minimum camera at the time of main / stop of the vehicle, and checks for real-time obstacles in front and rear of the vehicle and parking for real-time obstacles. It is possible to correct radiation distortion of a photographed image due to characteristics of a fish-eye lens by receiving an image from a camera including a.

The image output device 300 is a device capable of providing a user with a corrected image in the distortion image correction device 200, for example, a display device separately installed in a vehicle, a vehicle navigation or a terminal device, and the like. have.

The distortion image correcting apparatus according to an embodiment of the present invention has been described as an example of correcting distortion of an image photographed using a fisheye lens, but is not limited thereto, and any lens that can photograph a wide area image The lens is also applicable to the present invention.

In addition, the above-described camera 100, the distortion image correction device 200, and the image output device 300 are each independently implemented and can be connected through wired or wireless.

In addition, the distortion image correction device 200 may be implemented in a form embedded in the camera 100, or may be implemented in a form embedded in the image output device 300, the camera 100 and the distortion image correction device ( 200) and the image output device 300 may be implemented as one device.

Hereinafter, the main configuration and operation method of the distortion image correction apparatus 200 according to an embodiment of the present invention will be described.

2 is a block diagram showing a main configuration of a distortion image correction apparatus in an image processing system according to an embodiment of the present invention.

1 and 2, the distortion image correction apparatus 200 according to an embodiment of the present invention includes an image collection module 210, an image processing module 220, an image output module 230, and an image storage module 240 ).

When describing each component in more detail, first, the image collection module 210 serves to collect images captured through one or more cameras 100. Particularly, the image collection module 210 of the present invention collects images photographed through the camera 100 including a fish-eye lens. The images photographed through the camera 100 including a fish-eye lens are as described above. It also has radiation distortion.

That is, as shown in FIG. 3, the FOV model assumes that the distance between the center point C of the image and one point m on the image plane is proportional to the angle between the corresponding three-dimensional point M and the optical axis Cz, The distortion function of the FOV model can be defined as <Equation 1>.

는 왜곡된 거리를 나타내며,

는 렌즈의 왜곡이 없는 경우, 영상 중심에서 해당 픽셀까지의 거리를 나타낸다. 즉, 영상 중심에서 해당 픽셀까지의 거리

는 상기의 <수학식 1>에 의해 왜곡되어 왜곡된 거리

가 산출되는 것이며, 이때의

는 어안 렌즈의 화각으로, 카메라 내부 파라미터가 된다. 이상적인

는 1의 값을 가질 수 있다.here,

Denotes a distorted distance,

Indicates the distance from the center of the image to the corresponding pixel when there is no distortion of the lens. That is, the distance from the center of the image to the corresponding pixel

Is the distance distorted and distorted by Equation 1 above.

Is calculated,

Is the angle of view of the fish-eye lens, and is a parameter inside the camera. ideal

May have a value of 1.

The image collection module 210 may digitize an image collected in an analog form, for example, at a rate of 30 frames / s, and transmit the digitized image to the image processing module 220.

The image processing module 220 corrects the distortion of the image collected through the image collection module 210 to generate a corrected image. In particular, the image processing module 220 of the present invention optimizes the nonlinear region of the distorted image. After calculating the camera parameters, a distortion correction ratio is calculated based on the calculated camera parameters, and a correction image is generated by applying a distortion correction ratio to the collected image.

To this end, the image processing module 220 of the present invention may be configured to include an image pre-processing unit 221, a parameter calculating unit 222, and a corrected image generating unit 223.

In more detail, the image pre-processing unit 221 serves to match the long and short axis ratios of the images collected through the image collection module 210 before the distortion image is corrected.

를 계산하고, 이를 특징점 좌표 변환에 적용하여 비율을 일치시킨다. More specifically, since the fisheye lens is generally designed to have a larger horizontal angle of view than a vertical angle of view, a process of matching the long and short axis ratios of the image is necessary in a step prior to image correction. To this end, the image preprocessor 212 uses an ellipse-fitting algorithm to scale factors.

Is calculated and applied to the feature point coordinate transformation to match the ratio.

That is, as shown in FIG. 4, an image photographed through a fish-eye lens may be divided into a region in which an image is photographed and a peripheral region. In a region where an image is photographed, a specific number of feature points, for example, six feature points are extracted and , When this is connected, a certain area, that is, an ellipsoid can be obtained. Here, a variety of known techniques can be applied to the process of extracting the feature points.

) 및 단축(

)의 길이를 하기 <수학식 2>에 적용하여 스케일링 인자

를 계산하게 된다.Then, the long axis of the ellipsoid (

) And shortened (

) By applying the length to <Equation 2> below.

Will calculate

Here, since the adjusted image in which the ratio of the long axis and the short axis length of the input image is matched is randomly stretched, the edge (outer line) portion of the image has a non-linear shape.

The image pre-processing unit 221 transmits the adjusted image in which the ratio of the long axis and the short axis length of the input image is matched to the parameter calculating unit 222.

In addition, the image pre-processing unit 221 of the present invention can perform various image pre-processing such as noise removal, in addition to the role of matching the ratio of the long and short lengths of the image as described above.

For example, when the image pre-processing unit 221 receives an image composed of three channels of 8-bit color and RGB of 640 * 480 resolution, when performing image processing as the resolution of the received image, the calculation time becomes very long. Minimizing the width and height of the image, for example, can be reduced to 1/2 to perform image processing, and the received image can be converted into a black and white image. In addition, the image pre-processing unit 221 extracts the outline of the image using the binarized image data, and removes the area of the extracted outlines, for example, an area having a preset pixel, for example, an area of 1000 pixels or less as noise. You may.

The parameter calculating unit 222 calculates camera parameters for optimizing the nonlinear region of the image when an image having a length ratio of a long axis and a short axis is adjusted through the image pre-processing unit 221.

개의 특징점을 이용하게 되는데, 즉, 하기의 <수학식 3>의 영상(

)가 최소화되도록 카메라 파라미터(

)에 대한 최적값을 추정하게 된다.At this time, the image pre-processing unit 221 is calculated

The feature points of dogs are used, that is, the video of <Equation 3> (

) To minimize camera parameters (

).

은 왜곡되지 않은 점을 외부 파라미터

과

, 내부 파라미터

를 사용하여 왜곡시킨 점을 의미하는 것으로, 외부 파라미터 중

은 3x3의 회전 행렬을 의미하며,

는 3x1의 이동 행렬이 될 수 있다.here,

Is an external parameter

and

, Internal parameters

Means the point distorted by using, among the external parameters

Means 3x3 rotation matrix,

Can be a 3x1 moving matrix.

는 어안 렌즈의 화각이며,

는 어안 렌즈의 초점 거리(focal length)를 의미하며,

는 센서에 따른 변형을 나타내는 파라미터를 의미한다.Also, among the internal parameters

Is the angle of view of the fisheye lens,

Means the focal length of the fisheye lens,

Denotes a parameter representing deformation according to a sensor.

In more detail with respect to the above-described internal parameters and external parameters, a camera parameter according to an embodiment of the present invention may be configured as an internal parameter and an external parameter, which means a relationship between image coordinates and camera coordinates. As such, it can be determined at the time of manufacture of the camera. As for the internal parameters, values for a focal length, a skew vector, an optical center, and the like as described above may be internal parameters. On the other hand, the external parameter means a relationship between the camera coordinates and the spatial coordinates, and represents, for example, information about the rotation or movement of the camera. These external parameters may vary from time to time.

)를 카메라 초점을 기준으로 하는 카메라 좌표계(

)로 변환하게 되는 데, 외부 파라미터인 회전 행렬

과 이동 행렬

를 이용하여 하기의 <수학식 4>에 따라 수행하게 된다.The parameter calculating unit 222 is a real-world coordinate system (a virtual coordinate in 3D space) for calculating camera parameters of the applied image.

) Is the camera coordinate system based on the camera focus (

), Which is an external parameter, the rotation matrix.

And shift matrix

It is performed according to <Equation 4> below using.

)에서 2차원 영상으로 투영될 때, 이 둘 사이의 관계는 점 사영(point projection)에 기반한 핀홀(pin hole) 카메라 모델로 가정할 수 있는 데, 이때, 다양한 사영 기법 중 원근 사영(perspective projection)에 따라 원거리 물체는 작게, 근거리 물체는 크게 표현될 수 있다.Here, the camera coordinate system (

), When projected as a 2D image, the relationship between the two can be assumed to be a pinhole camera model based on point projection, where perspective projection among various projection techniques Depending on the distance object is small, the near object can be represented large.

는 사영 중심과 영상 평면 사이의 거리를 의미한다.Therefore, as shown in FIG. 5, by applying the following <Equation 5>, a three-dimensional point P = (Xc, Yc, Zc) to a point P '= (x, y) of the image plane Can be converted, and this is the internal parameter focal length

Means the distance between the projection center and the image plane.

In addition, finally, since the input image is digitized and stored, the characteristics of sensors such as a Charge Coupled Device (CCD) and Complementary Metal Oxide Semiconductor (CMOS) are affected.

Therefore, when the pixel to be stored is not square, the scaling factor K for the size of two coordinate axes of the image should be considered. In the conversion between the camera image coordinate system and the real image coordinate system, the deformation according to the sensor is calculated according to Equation 6 below considering the internal parameter K.

는 내부 파라미터로 이용하게 된다.In addition, as described with reference to Equation 1 above, the angle of view of the fish-eye lens is

Is used as an internal parameter.

Previously, the internal parameter may be a unique attribute value of the camera, and the external parameter may be different for each shooting.

That is, the focal length of the camera, which is an internal parameter, the degree of warpage, etc., is determined at the time of manufacture of the camera, and information about the rotation or movement of the camera, which is an external parameter, varies with each shooting. When calculating at the same time, there is a problem in that recalculation is required when changing the position or angle of the camera.

Therefore, in an embodiment of the present invention, the internal parameters are first calculated, and the external parameters are calculated each time the position and angle of the camera 100 are changed, thereby improving the speed of calculation.

개의 특징점을 추출한 후, 이를 이용하여 기 정의된 <수학식 3>을 이용하여 내부 파라미터를 먼저 산출하게 된다(S103). 여기까지가 파라미터 추출 1단계이다.That is, as shown in FIG. 6, when an image is input (S101), in an input image (an image obtained in the form of a two-dimensional 3D real world)

After extracting the feature points of the dog, the internal parameters are first calculated using <Equation 3> previously defined using this (S103). This is the first step of parameter extraction.

개의 특징점의 좌표와 S103 단계에서 산출된 내부 파라미터를 이용하여(S105) 외부 파라미터를 산출하게 된다(S107). 여기까지가 파라미터 추출 2단계로 이후, 카메라(100)의 위치 및 각도가 변경될 1단계는 생략하고 2단계만을 수행함으로써, 파라미터 산출 시의 연산 속도가 보다 더 빨라질 수 있다.Then, extracted from the input image

External parameters are calculated using the coordinates of the feature points and the internal parameters calculated in step S103 (S105) (S107). Up to this point, since the second step of parameter extraction, the first step in which the position and angle of the camera 100 is to be changed is omitted, and only the second step is performed, so that the calculation speed at the time of calculating the parameter can be faster.

The corrected image generating unit 223 serves to generate a final corrected image correcting the distortion of the image.

That is, a corrected image is generated by transforming coordinates using a predefined function such as <Equation 7> below for the distorted input image.

At this time, it is also possible to calculate the coordinates of the corrected image by applying a distortion correction ratio to the coordinates of the input image.

Here, the distortion correction ratio may be previously allocated according to the system setting.

)일 경우 하기의 <수학식 8>에 따라 왜곡 보정 후 영상 좌표의 위치에 따른 비율

를 계산하여 보정하게 된다.For example, the image size after distortion correction (

), The ratio according to the position of image coordinates after distortion correction according to <Equation 8> below

Is calculated and corrected.

, 즉 왜곡 영상의 중심에서 해당 픽셀까지의 거리가 길어져 역방향 사상으로 가져올 수 있는 정보가 적어 해상도가 낮아지게 되며, 퍼짐 현상 등 여러가지 문제로 인해 오히려 인지하기 어려운 결과 영상을 출력할 수 있다는 문제점이 있다.At this time, the distortion correction ratio is increased when it is closer to the center of the image, and the distortion correction ratio is decreased as it goes outward. This is when the image is corrected to the 2D plane by applying the pinhole camera model as described above in the input image with an angle of view of 180 ° or higher, as it goes outward

That is, as the distance from the center of the distorted image to the corresponding pixel becomes longer, there is less information that can be brought in the reverse direction, so the resolution is lowered. .

Therefore, the problem described above can be solved by increasing the distortion correction ratio when it is closer to the center of the image and by decreasing the distortion correction ratio toward the outside.

에서 왜곡 보정 비율 (

)를 조절하기 위해 하기의 <수학식 9>를 이용하여 왜곡 보정 비율을 산출할 수 있다.Also, the coordinates of the corrected image

Distortion correction ratio (

In order to adjust), the distortion correction ratio can be calculated using Equation 9 below.

는 사용자가 직접 입력할 수도 있다.Where the distortion constant

Can also be entered manually by the user.

Thereafter, the distortion correction ratio calculated through the above-described process may be applied to <Equation 10> below to generate a correction image reflecting the distortion correction ratio.

That is, the corrected image for the input image illustrated in FIG. 8 is illustrated in FIG. 9, and it can be confirmed that the nonlinear region is significantly reduced.

Distorted image correction device 200 of the present invention is an image storage module 240 for temporarily or permanently storing various images generated according to the process of the image processing module 220 and the image output device 300 for the corrected image It may be configured to further include a video output module 230 to transfer to the transfer.

At this time, the image storage module 240 stores various information generated in the process of generating the corrected image, for example, control information for driving the distortion image correcting apparatus 200 and images input from one or more cameras 100. In addition, it is possible to store a corrected image in which distortion of the image is corrected, or a camera parameter value calculated for each camera 100. The image storage module 240 includes optical media such as a hard disk, a floppy disk, and magnetic media such as a magnetic tape (Magnetic Media), a CD-ROM (Compact Disk Read Only Memory), and a DVD (Digital Video Disk). ), Magnetic-optical media such as a floppy disk, and ROM, random access memory (RAM), flash memory.

Then, the distortion image correction method in the image processing system configured as described above will be described in detail with reference to the accompanying drawings.

7 is a flowchart illustrating a distortion image correction method according to an embodiment of the present invention.

1 and 7, first, an image captured from one or more cameras 100 is received and input (1101). At this time, the input image may be a distorted image as illustrated in FIG. 8.

Subsequently, the distortion image correction apparatus 200 performs a process of matching the ratio of the long and short lengths of the input image (1102).

At this time, as described above, first, feature points of the input image are extracted. At this time, as shown in FIG. 8, an area in which an image exists and a peripheral area may be input together. After extracting a feature point from the region where the image exists, the feature points are connected to display an ellipsoid.

Thereafter, the lengths of the long and short axes of the region are calculated, and a scaling factor is calculated according to the ratio of the lengths of the long and short axes, and then the long axis is applied by applying a scaling factor of the region connected to the feature points, that is, the region corresponding to the ellipse. And the reduction ratio.

Thereafter, camera parameters are calculated to optimize the generated nonlinear region of the adjusted image (1103).

The camera parameter includes an internal parameter and an external parameter. As described above, the value of each parameter is estimated so that the result value of <Equation 3> becomes minimum. Here, when calculating parameters, first, internal parameters may be calculated, and external parameters may be calculated using the coordinates of the internal parameters and feature points of the input image.

Thereafter, to generate a corrected image, a distortion correction ratio is calculated using the camera parameter, and a distortion correction ratio is applied to the adjusted image having long and short axis lengths adjusted (1104), thereby generating a corrected image (1105). ).

When generating the corrected image, a corrected image may be generated by adjusting a distortion correction ratio according to a distance from the center point based on the center point of the adjusted image.

Thereafter, when the corrected image is transmitted to the image output device 300, the received image output device 300 may output the corrected image (1106).

The distortion image correction method according to the embodiment of the present invention has been described above.

The distortion image correction method as described above, by enabling to derive the image most similar to the real from the image taken through the fish-eye lens, to accurately calculate the distance between the camera and the target using the information of the correction image , As a result, it is applied to a vehicle parking system, so that obstacle recognition, surrounding space security, and situation control can be implemented.

In addition, the distortion image correction method may be implemented as a program and implemented in a computer-readable recording medium.

The program instructions recorded to execute the distortion image correction method according to the present invention may be specially designed and configured for the present invention, or may be known and available to those skilled in computer software. For example, recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes (Magnetic Media), compact disk read only memory (CD-ROM), optical media such as DVD (Digital Video Disk), and optical media. Includes magneto-optical media, such as a floppy disk, and hardware devices specifically configured to store and execute program instructions such as ROM, random access memory (RAM), flash memory, etc. do. Examples of program instructions may include high-level language code that can be executed by a computer using an interpreter, etc., as well as machine language codes made by a compiler. Such a hardware device may be configured to operate as one or more software modules to perform the operation of the present invention, and vice versa.

On the other hand, the embodiments of the present invention disclosed in the specification and drawings are merely presented as specific examples for ease of understanding, and are not intended to limit the scope of the present invention. It is obvious to those skilled in the art to which the present invention pertains that other modified examples based on the technical idea of the present invention can be implemented in addition to the embodiments disclosed herein.

The present invention relates to distortion image correction, in particular, by optimizing the nonlinear region of the image taken through the fisheye lens to generate a corrected image, it is possible to minimize the difference between the image taken through the fisheye lens and the actual shooting object. It is a useful invention that generates the effect of providing a more realistic image, thereby contributing to the development of the service industry.

100: camera 200: distortion image correction device 210: image acquisition module
220: image processing module 221: image pre-processing unit
222: parameter calculation unit 223: correction image generation unit
230: video output module 240: video storage module
300: video output device

Claims (8)

An image pre-processing unit that generates an adjusted image by matching a long axis and a short axis ratio of the input image;
A parameter calculating unit calculating camera parameters for correcting a nonlinear region formed in the adjusted image due to the adjustment of the long and short axis ratios of the image preprocessing unit; And
A correction image generation unit that generates a correction image by applying the calculated camera parameters to the adjusted image;
Distorted image correction device comprising a. ◈ Claim 2 was abandoned when payment of the registration fee was set.◈ According to claim 1,
The image pre-processing unit
After extracting the feature points of the input image, check the long axis and short axis length of the region to which the feature points are connected, calculate the scaling factor using the long axis and short axis length, and apply them to the input image to apply the long and short axis ratios of the input image Distorted image correction device, characterized in that for adjusting. ◈ Claim 3 was abandoned when payment of the set registration fee was made.◈ According to claim 2,
The image pre-processing unit,
Distortion image correction device characterized in that for extracting the feature points of the input image, and connecting the feature points to obtain an ellipsoid. ◈ Claim 4 was abandoned when payment of the set registration fee was made.◈ According to claim 3,
The Yeongsan pre-processing unit,
Distorted image correction apparatus characterized in that the scaling factor is calculated by applying the lengths of the major axis and the minor axis of the ellipsoid to the following equation.
[Mathematics]

(Here, the long axis

, Shorten

to be. ◈ Claim 5 was abandoned when payment of the set registration fee was made.◈ According to claim 1,
The parameter calculation unit
Distortion image correction device, characterized in that for calculating a camera parameter to minimize the value of a predefined function using the feature points calculated through the image pre-processing unit. ◈ Claim 6 was abandoned when payment of the set registration fee was made.◈ According to claim 1,
The correction image generation unit,
In the adjusted image, a correction image is generated by calculating a distortion correction ratio using a camera parameter calculated through the parameter calculation unit, and a correction image is adjusted by adjusting a distortion correction ratio according to a distance from a center point based on the adjusted image center point. Distortion image correction device characterized in that for generating. A distortion image correcting apparatus generating an adjusted image by matching a long axis and a short axis ratio of the input image;
Calculating, by the distortion image correction apparatus, a parameter for correcting a nonlinear region formed in the adjusted image due to the adjustment of the long and short axis ratios;
Generating, by the distortion filtering apparatus, a correction image by applying the calculated parameter to the adjusted image;
Distorted image correction method comprising a. A computer-readable recording medium comprising a program for executing the distortion image correction method according to claim 7.

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