OBJECT IDENTIFICATION DEVICE, MOVING OBJECT CONTROLLING APPARATUS HAVING OBJECT IDENTIFICATION DEVICE, INFORMATION PRESENTING APPARATUS HAVING OBJECT IDENTIFICATION DEVICE, AND SPECTROSCOPIC IMAGE CAPTURING APPARATUS

• US 20120069181A1
• Filed: 09/12/2011
• Published: 03/22/2012
• Est. Priority Date: 09/16/2010
• Status: Active Grant

• Current Assignee: Ricoh Company Limited
• Original Assignee: Ricoh Company Limited
• Inventors: Hirai, Hideaki, XUE, Li
• Granted Patent: US 9,025,027 B2
• Time in Patent Office: Days
• US Class Current: 348/148
• CPC Class Codes: G01J 3/0229 using masks, aperture plates, spatial light modulators or spatial filters, e.g. reflective filters
• CPC Class Codes: G01J 3/28 Investigating the spectrum using colour filters G01J3/51
• CPC Class Codes: G01J 3/447 Polarisation spectrometry
• CPC Class Codes: G01J 3/453 by correlation of the amplitudes
• CPC Class Codes: G01J 9/0246 Measuring optical wavelength
• CPC Class Codes: G01N 21/314 with comparison of measurements at specific and non-specific wavelengths dual wavelength spectrometry G01J3/427
• CPC Class Codes: G06T 5/50 using two or more images, e.g. averaging or subtraction
• CPC Class Codes: G06T 5/70 Denoising; Smoothing
• CPC Class Codes: G06V 10/143 Sensing or illuminating at different wavelengths
• CPC Class Codes: G06V 20/58 Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
• CPC Class Codes: G06V 20/584 of vehicle lights or traffic lights
• CPC Class Codes: G06V 20/588 Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road
• CPC Class Codes: G08G 1/16 Anti-collision systems road vehicle drive control systems for predicting or avoiding probable or impending collision otherwise than by control of a particular sub-unit B60W30/08
• CPC Class Codes: G08G 1/165 for passive traffic, e.g. including static obstacles, trees
• CPC Class Codes: G08G 1/166 for active traffic, e.g. moving vehicles, pedestrians, bikes
• CPC Class Codes: G08G 1/167 Driving aids for lane monitoring, lane changing, e.g. blind spot detection

Abstract

An object identification device includes an image capturing device to capture images polarized in different directions. A noise removal unit removes noise in the polarized images using a noise removing parameter. An index value computing unit computes an object identification index value for identification-processing areas in the polarized images using data of noise-removed polarized images. An object identification processing unit conducts object identification by determining identification processing areas corresponding to an identification target object based on the object identification index value. An environment information obtaining unit obtains environment information. An environmental condition determination unit determines an environmental condition based on the environment information. A parameter storage unit stores noise removing parameters prepared for mutually exclusive environmental conditions. The noise removal unit reads a noise removing parameter from the parameter storage unit to conduct noise removal. A method of identifying an object and a spectroscopic image capturing apparatus are also provided.

Claims

1. An object identification device, comprising:

an image capturing device to receive polarized light polarized in two different directions included in light reflected from an object in an image capturing area and capture two polarized images, one polarized image for each type of polarized light;

a noise removal unit to remove a noise component included in each of the two polarized images captured by the image capturing device, using a noise removing parameter;

an index value computing unit to divide each of the two polarized images captured by the image capturing device into identification-processing areas to compute an object identification index value for each of the identification-processing areas using light intensity data of each of the two polarized images from which the noise component is removed by the noise removal unit;

an object identification processing unit that conducts an object identification process that determines a plurality of identification processing areas corresponding to an identification target object based on the object identification index value of each of the identification processing areas computed by the index value computing unit, and identifies a plurality of adjacent identification processing areas as the identification processing areas corresponding to the identification target object as an image area of the identification target object;

an environment information obtaining unit to obtain environment information to determine an environmental condition of an object in an image capturing area;

an environmental condition determination unit to determine an environmental condition of the object in the image capturing area based on the environment information obtained by the environment information obtaining unit; and

a parameter storage unit to store one or more noise removing parameters to remove a noise component included in the two polarized images captured under an environmental condition determined by the environmental condition determination unit, each noise removing parameter being prepared and stored for one of a plurality of mutually exclusive environmental conditions,

wherein the noise removal unit reads out a noise removing parameter for the environmental condition determined by the environmental condition determination unit from the parameter storage unit, and conducts the noise removing process using the noise removing parameter.

2. The object identification device of claim 1, wherein the noise removing parameter is a threshold value to determine whether light intensity data included in the two polarized images is a noise component,

wherein the noise removing process comprises determining whether the light intensity data included in the two polarized images captured by the image capturing device is a noise component based on the threshold value specified by the noise removing parameter, and removing the light intensity data identified as a noise component from computation of the object identification index value by the index value computing unit.

3. The object identification device of claim 2, wherein a light intensity difference between a target pixel and surrounding pixels surrounding the target pixel in the two polarized images that exceeds the threshold value specified by the noise removing parameter causes the impulse noise removing process to identify the light intensity data of the surrounding pixels as a noise component and remove the light intensity data of the surrounding pixels.

4. The object identification device of claim 3, wherein, after conducting the impulse noise removing process, the noise removing process comprises removing high-frequency noise included in light intensity data in the noise removing processing area defined by the target pixel and the surrounding pixels based on light intensity data of the target pixel and light intensity data of the surrounding pixels surrounding the target pixel in the two polarization images.

5. The object identification device of claim 1, wherein the noise removing parameter set for each of the environmental conditions and stored in the parameter storage unit is obtained by taking a plurality of polarized light sample images and obtaining two polarized images for a plurality of image capturing areas under one environmental condition and adjusting to a value to remove a noise component in the two polarized images captured under the environmental condition with a high precision when conducting the noise removing processing.

6. The object identification device of claim 1, wherein the object identification index value employs a polarized light ratio for each of the identification processing areas that is a ratio of light intensity data between two polarized images captured by the image capturing images.

7. The object identification device of claim 1, wherein the object identification index value employs a polarization intensity difference for each of the identification processing areas that is a ratio between a difference in light intensity between the two polarized images and a total light intensity of the two polarized images captured by the image capturing device.

8. The object identification device of claim 7, wherein the environment information obtaining unit obtains the object identification index value, computed by the index value computing unit, as the environment information, and the environmental condition determination unit determines an environmental condition of an object in an image capturing area based on the object identification index value obtained by the environment information obtaining unit.

9. The object identification device of claim 8, wherein the environmental condition determination unit determines an environmental condition of an object in an image capturing area based on a variation among object identification index values measured at a plurality of points in the image capturing area.

10. A moving object control apparatus, comprising:

the object identification device according to claim 1; and

a movement control unit to conduct movement control of the moving object using an identification result produced by the object identification device according to claim 1.

11. An information presenting apparatus, comprising:

the object identification device according to claim 1 to capture scenes surrounding a vehicle as an image capturing area to identify an object existing in the image capturing area;

a useful information generating unit to generate useful information for an operator of the vehicle using an identification result of the object identification device; and

an information reporting unit to report the information generated by the useful information generating unit to the operator.

12. A method of identifying an object, comprising the steps of:

receiving light polarized in two different polarization directions included in light reflected from an object in an image capturing area using an image capturing device and capturing a polarized image for each of the two types of polarized light using the image capturing device;

dividing each of the two polarized images captured by the image capturing device into identification processing areas to compute an object identification index value for each of the identification processing areas using an index value computing unit using light intensity data of each of the two polarized images from which the noise component has been removed by the noise removal unit;

determining identification processing areas corresponding to an identification target object using an object identification processing unit based on the object identification index value of each of the identification processing areas computed by the index value computing unit;

conducting an object identification process in which the object identification processing unit identifies a plurality of adjacent identification processing areas determined as the identification processing areas corresponding to the identification target object as an image area of the identification target object;

obtaining environment information to determine an environmental condition of an object in the image capturing area using an environment information obtaining unit;

determining an environmental condition of the object existing in the image capturing area based on the environment information obtained by the environment information obtaining unit;

storing a plurality of noise removing parameters in a parameter storage unit, each of the noise removing parameters being prepared and stored for a plurality of mutually exclusive environmental conditions;

reading out one noise removing parameter from among the plurality of noise removing parameters stored in the parameter storage unit for the environmental condition determined by the environmental condition determination unit to remove a noise component included in the two polarized images captured under the environmental condition; and

removing the noise component included in the two polarized images captured under the environmental condition determined by the environmental condition determination unit using the noise removing parameter read from the parameter storage unit.

13. A spectroscopic image capturing apparatus for obtaining a two-dimensional spectroscopic image correlating each point in an image capturing area with wavelength information measured at each point, the spectroscopic image capturing apparatus comprising:

an optical filter;

an image sensor having a two-dimensionally arranged pixel array to receive and detect light from an image capturing area via the optical filter and output a detection result,

wherein the optical filter includes a diffraction grating having a grid pattern, in which one grid area corresponds to one unit area defined on the image sensor, the one unit area being composed of one or more pixels;

an image generator to generate a difference-value-based image based on a difference value between received light intensity of one unit area and received light intensity of another adjacent unit area, the difference value computable based on the detection result of the image sensor, in which an interference level on the image sensor changes at each point depending on a diffraction angle of light passing the diffraction grating; and

a noise removal unit to remove a noise component included in the difference-value-based image generated by the image generator using a noise removing parameter.

14. The spectroscopic image capturing apparatus of 13, further comprising a parameter storage unit to store a plurality of noise removing parameters to remove a noise component included in the difference-value-based image generated by the image generator, each noise removing parameter being prepared for a respective one of a plurality of wavelengths,

wherein the noise removal unit reads out a noise removing parameter for a given wavelength for a noise removing area in the difference-value-based image generated by the image generator from the parameter storage unit, and removes noise using the noise removing parameter.

15. The spectroscopic image capturing apparatus of 13, wherein the noise removing parameter is a threshold value to determine whether a difference value of the difference-value-based image, generated by the image generator, is a noise component,

wherein a difference value between a target unit area and a surrounding unit area surrounding the target unit in the difference-value-based image area that exceeds the threshold value specified by the noise removing parameter causes the difference value for the surrounding unit area to be identified as a noise component that is then removed.