JP3704564B2 - Method and apparatus for determining road surface condition at night by visible image - Google Patents
Method and apparatus for determining road surface condition at night by visible image Download PDFInfo
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Description
【０００１】
【発明の属する技術分野】
この発明は、可視画像による夜間における路面状況判定方法およびその装置、さらに詳しくは道路上に設置した監視カメラの映像を入力し、その画像を処理することにより、道路路面の乾燥、湿潤、水膜、積雪の４状態を判定する路面状況判定に関する。
【０００２】
【従来の技術】
昼夜連続で路面状況を画像処理で判定する場合は、撮像装置として路面に赤外線やレーザを照射し、路面からの正反射および乱反射成分を検出し、この受光レベルにより路面の状態を判別する方法が提案されている。また、可視画像で路面状況を判別する方法も提案されている（例えば、特許文献１参照。）。
【０００３】
【特許文献１】
特開２００２−１４０７８９号公報（第２，３頁、図１）
【０００４】
しかしながら、前者の場合は、特殊な装置を道路上の施設として設置する必要があり、また後者の場合、例えば、特許文献１のような可視画像により路面状況を判定する場合は、夜間において可視カメラで撮像された映像では十分な輝度が確保できず、昼間だけしか路面状況の判定を行うことができなかった。
【０００５】
【発明が解決しようとする課題】
そこで、この発明は、特許文献１のような可視画像により路面状況を判定する方法に加えて、車両や歩行者の安全性を確保するために数多く設置されている道路照明灯に対する道路監視のための可視カメラ設置条件とその時の撮像条件を満たし、その条件の上で得られる可視カメラから得られる映像を取り込み、この映像より取得したビットマップ画像を画像処理することにより、道路上に新たな設備を追加することなく、昼夜間連続で路面の状態を判断する方法とその装置を提供することを目的とする。
【０００７】
【課題を解決するための手段】
前記目的を達成するため、請求項１に記載の発明は、道路照明灯が設置されている路面の路面状況を判定する路面状況判定装置であって、前記道路照明灯と対向して設置された道路監視用カメラから得られる映像を、ビットマップ画像に変換し、このビットマップ画像から得られる可視光成分を輝度画像に変換する画像変換手段と、この画像変換手段により変換された輝度画像において、前記道路照明灯の光源が前記道路監視用カメラに撮像されたときの鏡面反射となることに基づき算出された乾燥、湿潤、水膜、積雪の、前記道路照明灯と水膜検出位置を結ぶ線分に基づく領域である判定領域をそれぞれ求める手段と、その各判定領域内の輝度平均を算出する画像特徴量算出手段と、その各画像特徴量を比較する手段と、前記各画像特徴量から路面状態を判定する判定手段とを具え、前記判定手段は、前記各画像特徴量を比較する手段が前記判定領域毎の画像特徴量を比較した結果に基づき、水膜路面時の画像特徴量が乾燥、積雪路面時の画像特徴量よりも大きいとき路面は水膜状態、湿潤路面の時の画像特徴量が乾燥、積雪路面時の画像特徴量よりも大きいとき路面は湿潤状態、前記路面状態のいずれにも該当せず、かつ予め計測された乾燥路面時の画像特徴量である閾値より大きいとき路面は積雪状態、前記路面状態のいずれにも該当しないとき、路面は乾燥状態であると判定する。請求項２に記載の発明は、請求項１に記載の発明において、道路照明灯に対する道路監視用カメラの設置条件と撮像条件が、路面状態による道路照明灯光源の反射位置から求められる。
【０００８】
【発明の実施の形態】
以下、一実施の形態について、添付図面に基づいて詳細に述べる。
【０００９】
図１は、実施の形態における道路照明灯に対する道路監視用カメラの位置関係を示したものである。道路照明灯と道路監視用カメラの水平面上で両者を結んだ線分の路面上に検出対象が存在している状況で、その路面状況が水膜である場合、光源の反射光は鏡面反射成分のみが観測される。路面状況が湿潤である場合、光源の反射光は路面凹凸に溜まった水分による鏡面反射成分が観測され、水膜時の鏡面反射位置から道路照明灯に向かって延びる。路面状況が乾燥、積雪の場合、光源の反射光は拡散光のみが観測され、照明灯柱に近い周辺に観測される。積雪時は乾燥時と比較して雪結晶により拡散光を強く放出するため、広い領域で観測される。
【００１０】
乾燥時、積雪時の反射光発生位置は道路照明灯位置で求められ、湿潤時の反射光は水膜時の反射光発生位置から求められるため、水膜時の反射光発生位置を求めれば４状態時全ての反射光発生位置が求められる。
【００１１】
図２は、道路照明灯に対する道路監視用カメラの位置関係を道路照明灯と道路監視用カメラの水平面上で両者を結んだ線分上の断面図で示したものである。この図において、水膜の反射光発生位置は、道路照明灯の光源が道路監視用カメラに撮像された時の鏡面反射となる位置となるから、正反射の条件、すなわちθ１＝θ２であり、道路照明灯から道路監視用カメラまでの距離をLとすると、式（１）により算出される。
【００１２】
【数１】
h1：道路監視用カメラの高さ
h2：道路照明灯の高さ
ｘ：道路照明灯の光源が道路監視用カメラに撮像された時の鏡面反射となる位置
【００１３】
従って、道路監視用カメラの設置条件は、次のようになる。
・道路監視用カメラは道路照明灯から式（１）に示す距離Ｌをとる。
・式（１）中のｘの位置に検出対象路面がある。
【００１４】
また、図３は、設置条件を満たす場合に道路監視用カメラで撮像した夜間の路面映像である。設置条件を満たす道路監視用カメラにおける撮像条件は、道路照明灯の反射輝度がどの路面状態の時でも撮像されることである。このとき、式（１）を変形して、道路照明灯の光源が道路監視用カメラに撮像された時の鏡面反射となる位置ｘを求める式（２）を得る。
【００１５】
【数２】
h1：道路監視用カメラの高さ
h2：道路照明灯の高さ
L：道路照明灯から道路監視用カメラまでの距離
【００１６】
昼間の路面状態判定と同じ撮像条件とすることを条件に加えると、道路横断方向の撮像範囲は路面全体が収まるようにすれば良い。以上を整理して、撮像条件は次の条件の全てを満たす場合である。
・撮像範囲の道路横断方向は、検出対象とする路面全体を含める。
・撮像範囲の道路縦断方向下端は、図１における反射光の輝度の観測位置が水膜の場合に（２）式で示された位置の路面が撮像範囲内となっていること。
・撮像範囲の道路縦断方向上端は、図１における反射光の輝度の観測位置が乾燥、積雪時に観測される照明灯柱に近い周辺の路面が撮像範囲内となっていること。
【００１７】
図４は、実施の形態における路面状況監視装置のブロック図である。図４において、１１は前記設置条件と撮像条件を満たして設置された道路監視用の可視カメラ、１２は可視カメラからの映像をビットマップ画像に変換するＡＤ変換部、１３はビットマップ画像を輝度画像に変換する画像変換部、１４は輝度画像から各路面状態別の判定量を算出するための領域別に輝度平均の画像特徴量を算出する画像演算部、１５は各画像特徴量から路面状態を判定して出力する判定部である。
【００１８】
次に主要部分である、画像演算部１４と判定部１５について説明する。
【００１９】
画像演算部１４では輝度画像から画像特量を算出する。画像特徴量の算出方法は、まず、輝度画像のうち、道路照明灯と水膜検出位置を結ぶ線分上の輝度値を取得する。線分の輝度値を、道路照明灯設置位置を原点としてグラフ上に表したものが図５である。
【００２０】
図５において、区間１は乾燥、積雪状態時の輝度観測位置、区間２は湿潤状態時の輝度観測位置、区間３は水膜時の輝度観測位置である。ここで各区間の求め方について述べる。区間１は道路照明灯の路面での反射光のうち、拡散光が道路監視用カメラで撮像された時に発生する輝度値であるから、道路用照明灯の設置高さによる距離別照度分布を予め計測しておくことにより求まる。また、区間２は区間１と区間３の間であり、区間３の中心は前記（２）式で求めたｘである。図５で各区間それぞれの輝度値の合計を区間長で割ったもの、すなわち区間毎の輝度平均を求める。以上が画像演算部１４で求める画像特徴量である。
【００２１】
次に判定部１５では、画像演算部１４で求めた画像特徴量から路面状態を判定して出力する。区間毎の画像特徴量から、次の判定条件により路面の４状態を判定する。
▲１▼ 区間３画像特徴量＞区間１画像特徴量の場合は水膜状態
▲２▼ 区間２画像特徴量＞区間１画像特徴量の場合は湿潤状態
▲３▼ 上記どれにも当てはまらない場合、区間１画像特徴量＞閾値の場合は積雪状態、
▲４▼ そうでなければ乾燥状態
ここで閾値は乾燥時の画像特徴量を予め計測しておくことにより求める。
【００２２】
【発明の効果】
以上のように、この発明によれば、可視画像により路面状況を判定する方法に加えて、車両や歩行者の安全性を確保するために数多く設置されている道路照明灯に対する道路監視のための可視カメラ設置条件とその時の撮像条件を満たし、その条件の上で得られる可視カメラから得られる映像を取り込み、この映像より取得したビットマップ画像を画像処理することにより、道路上に新たな設備を追加することなく、昼夜間連続で路面の状態を判断することができるという優れた効果がある。
【図面の簡単な説明】
【図１】この発明の一実施の形態を示す道路照明灯に対する道路監視用カメラの位置関係を説明するための平面図である。
【図２】同上の道路照明灯に対する道路監視用カメラの位置関係を説明するための側面図である。
【図３】同上の撮像映像の例を示す図である。
【図４】同上の路面状況監視装置のブロック図である。
【図５】同上の画像特徴量の例を示す図である。
【符号の説明】
１１ 可視カメラ
１２ ＡＤ変換部
１３ 画像変換部
１４ 画像演算部
１５ 判定部[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a night road surface condition determination method and apparatus based on a visible image, and more specifically, by inputting a video of a surveillance camera installed on a road, and processing the image to dry, wet and water film on the road surface. The present invention relates to road surface condition determination for determining four snow conditions.
[0002]
[Prior art]
When determining the road surface condition by image processing continuously day and night, there is a method of irradiating the road surface with infrared rays or a laser as an imaging device, detecting regular reflection and irregular reflection components from the road surface, and determining the road surface state based on this received light level. Proposed. In addition, a method for discriminating a road surface condition from a visible image has been proposed (see, for example, Patent Document 1).
[0003]
[Patent Document 1]
Japanese Patent Laid-Open No. 2002-140789 (pages 2, 3 and 1)
[0004]
However, in the former case, it is necessary to install a special device as a facility on the road. In the latter case, for example, when the road surface condition is determined by a visible image as in Patent Document 1, a visible camera is used at night. In the video captured in the above, sufficient brightness could not be secured, and the road surface condition could be determined only during the daytime.
[0005]
[Problems to be solved by the invention]
In view of this, the present invention is not limited to the method of determining the road surface condition from the visible image as in Patent Document 1, but for road monitoring of many road lighting lamps installed to ensure the safety of vehicles and pedestrians. New equipment on the road by capturing the video obtained from the visible camera that meets the conditions and the imaging conditions at that time, and processing the bitmap image obtained from this video An object of the present invention is to provide a method and an apparatus for determining a road surface state continuously day and night without adding a sash.
[0007]
[Means for Solving the Problems]
In order to achieve the above object, the invention according to claim 1 is a road surface condition judging device for judging a road surface condition of a road surface on which a road illumination light is installed, and is installed facing the road illumination light. In the luminance image converted by the image conversion means for converting the video obtained from the road monitoring camera into a bitmap image and converting the visible light component obtained from the bitmap image into the luminance image, A line connecting the road illumination light and the water film detection position of dry, wet, water film, and snow calculated based on the specular reflection when the light source of the road illumination light is captured by the road monitoring camera means for determining respective determination area which is an area based on the minute, and the image feature quantity calculating means for calculating an average luminance of each determination area, and means for comparing the respective image feature amount, the respective image feature amount Determining means for determining the road surface state, wherein the determining means compares the image feature values for each determination area by the means for comparing the image feature values, and the image feature values for the water film road surface Is larger than the image feature amount on the dry and snowy road surface, the road surface is in a water film state, and when the image feature amount on the wet road surface is larger than the image feature amount on the dry and snowy road surface, the road surface is in a wet state. If the road surface is larger than a threshold that is a pre-measured image feature value on a dry road surface, the road surface is determined to be in a dry state when the road surface does not fall into any of the above-described snow conditions and the road surface state. To do . According to a second aspect of the present invention, in the first aspect of the invention , the installation condition and the imaging condition of the road monitoring camera with respect to the road illumination lamp are obtained from the reflection position of the road illumination light source according to the road surface condition.
[0008]
DETAILED DESCRIPTION OF THE INVENTION
Hereinafter, an embodiment will be described in detail with reference to the accompanying drawings.
[0009]
FIG. 1 shows the positional relationship of a road monitoring camera with respect to a road illumination lamp in the embodiment. When the detection target exists on the road surface of the line connecting the road lighting and the road surveillance camera on the horizontal plane, and the road surface condition is a water film, the reflected light of the light source is the specular reflection component Only observed. When the road surface condition is wet, the reflected light of the light source is observed to have a specular reflection component due to moisture accumulated on the road surface unevenness, and extends from the mirror reflection position at the time of the water film toward the road illumination lamp. When the road surface condition is dry or snowy, only the diffused light is observed as the reflected light from the light source, and it is observed in the vicinity of the lighting pole. Compared with dry season, when snow falls, the diffused light is emitted more strongly by snow crystals, so it is observed in a wider area.
[0010]
Since the reflected light generation position at the time of drying and snow accumulation is obtained from the position of the road illumination lamp, and the reflected light at the time of wetness is obtained from the reflected light generation position at the time of the water film, 4 is obtained if the reflected light generation position at the time of the water film is obtained. All reflected light generation positions are obtained in the state.
[0011]
FIG. 2 shows the positional relationship of the road monitoring camera with respect to the road illumination lamp as a cross-sectional view on a line segment connecting the road illumination lamp and the road surveillance camera on the horizontal plane. In this figure, the reflected light generation position of the water film is a position that becomes a specular reflection when the light source of the road illuminating lamp is imaged by the road monitoring camera, so the condition of regular reflection, that is, θ1 = θ2. When the distance from the road illumination lamp to the road monitoring camera is L, it is calculated by the equation (1).
[0012]
[Expression 1]
h1: Height of camera for road monitoring
h2: the height of the road illumination light x: the position that becomes the specular reflection when the light source of the road illumination light is captured by the road surveillance camera
Therefore, the installation conditions of the road monitoring camera are as follows.
The road monitoring camera takes the distance L shown in the equation (1) from the road lighting.
-There exists a detection target road surface in the position of x in Formula (1).
[0014]
FIG. 3 is a night road surface image captured by a road monitoring camera when the installation condition is satisfied. The imaging condition of the road monitoring camera that satisfies the installation condition is that the imaging is performed regardless of the road surface condition of the reflected luminance of the road illumination lamp. At this time, the equation (1) is modified to obtain the equation (2) for obtaining the position x that becomes the specular reflection when the light source of the road illumination light is imaged by the road monitoring camera.
[0015]
[Expression 2]
h1: Height of camera for road monitoring
h2: Height of road lighting
L: Distance from the road lighting to the road surveillance camera [0016]
If the same imaging conditions as those for daytime road surface condition determination are added to the condition, the imaging range in the road crossing direction may be set so that the entire road surface is accommodated. Arranging the above, the imaging conditions satisfy all of the following conditions.
-The road crossing direction of the imaging range includes the entire road surface to be detected.
The road surface in the longitudinal direction of the imaging range is such that the road surface at the position indicated by equation (2) is within the imaging range when the reflected light brightness observation position in FIG. 1 is a water film.
-At the upper end of the imaging range in the longitudinal direction of the road, the observation position of the reflected light brightness in FIG. 1 is dry, and the road surface around the illuminating lamp column observed during snow accumulation is within the imaging range.
[0017]
FIG. 4 is a block diagram of a road surface condition monitoring apparatus according to the embodiment. In FIG. 4, reference numeral 11 denotes a road monitoring visible camera installed so as to satisfy the installation conditions and the imaging conditions, 12 denotes an AD conversion unit that converts a video from the visible camera into a bitmap image, and 13 denotes a luminance of the bitmap image. An image conversion unit for converting to an image, 14 is an image calculation unit for calculating an image feature amount of average luminance for each region for calculating a determination amount for each road surface state from the luminance image, and 15 is a road surface state from each image feature amount. It is the determination part which determines and outputs.
[0018]
Next, the
[0019]
The
[0020]
In FIG. 5, section 1 is a brightness observation position in a dry and snowy state, section 2 is a brightness observation position in a wet state, and section 3 is a brightness observation position in a water film. Here, how to obtain each section is described. Since section 1 is a luminance value generated when diffused light is captured by the road monitoring camera among the reflected light on the road surface of the road lamp, the illuminance distribution according to distance depending on the installation height of the road lamp is preliminarily determined. It is obtained by measuring. The section 2 is between the sections 1 and 3, and the center of the section 3 is x obtained by the above equation (2). In FIG. 5, the sum of the luminance values of each section divided by the section length, that is, the average brightness for each section is obtained. The above is the image feature amount obtained by the
[0021]
Next, the
(1) If the section 3 image feature amount> section 1 image feature amount, the water film state. (2) If the section 2 image feature amount> section 1 image feature amount, the wet state. (3) If none of the above applies, If section 1 image feature value> threshold value, snow condition,
(4) Otherwise, dry state Here, the threshold value is obtained by measuring the image feature amount at the time of drying in advance.
[0022]
【The invention's effect】
As described above, according to the present invention, in addition to the method for determining the road surface condition from the visible image, for road monitoring of many road illumination lights installed to ensure the safety of vehicles and pedestrians. New equipment is installed on the road by capturing the video obtained from the visible camera that meets the conditions for setting the visible camera and the imaging conditions at that time, and processing the bitmap image obtained from this video. There is an excellent effect that the state of the road surface can be determined continuously day and night without adding.
[Brief description of the drawings]
FIG. 1 is a plan view for explaining the positional relationship of a road monitoring camera with respect to a road illumination lamp according to an embodiment of the present invention.
FIG. 2 is a side view for explaining the positional relationship of the road monitoring camera with respect to the road illumination lamp.
FIG. 3 is a diagram showing an example of a captured image same as above.
FIG. 4 is a block diagram of the above road surface condition monitoring apparatus.
FIG. 5 is a diagram showing an example of the image feature amount of the above.
[Explanation of symbols]
11
Claims (2)
前記道路照明灯と対向して設置された道路監視用カメラから得られる映像を、ビットマップ画像に変換し、このビットマップ画像から得られる可視光成分を輝度画像に変換する画像変換手段と、この画像変換手段により変換された輝度画像において、前記道路照明灯の光源が前記道路監視用カメラに撮像されたときの鏡面反射となることに基づき算出された乾燥、湿潤、水膜、積雪の、前記道路照明灯と水膜検出位置を結ぶ線分に基づく領域である判定領域をそれぞれ求める手段と、その各判定領域内の輝度平均を算出する画像特徴量算出手段と、その各画像特徴量を比較する手段と、前記各画像特徴量から路面状態を判定する判定手段とを具え、
前記判定手段は、前記各画像特徴量を比較する手段が前記判定領域毎の画像特徴量を比較した結果に基づき、水膜路面時の画像特徴量が乾燥、積雪路面時の画像特徴量よりも大きいとき路面は水膜状態、湿潤路面の時の画像特徴量が乾燥、積雪路面時の画像特徴量よりも大きいとき路面は湿潤状態、前記路面状態のいずれにも該当せず、かつ予め計測された乾燥路面時の画像特徴量である閾値より大きいとき路面は積雪状態、前記路面状態のいずれにも該当しないとき、路面は乾燥状態であると判定することを特徴とする路面状況判定装置。 A road surface condition determination device for determining a road surface condition of a road surface on which a road illumination light is installed,
An image conversion means for converting a video obtained from a road monitoring camera installed facing the road illumination light into a bitmap image, and converting a visible light component obtained from the bitmap image into a luminance image; and in transformed luminance image by the image conversion means, drying the light source of the street lighting lamps is calculated on the basis that the specular reflection when captured in the surveillance camera, wet, water film, snow, the comparison means for determining respective determination area which is an area that is based on the line segment, and the image feature quantity calculating means for calculating an average luminance of each determination area, the respective image feature amounts connecting road lighting and water film detection position And means for determining a road surface state from each image feature amount,
The determination means is based on a result of comparing the image feature amounts for each determination region by the means for comparing the image feature amounts, and the image feature amount on the water film road surface is dry and is more than the image feature amount on the snowy road surface. When the road surface is large, the road surface is in a water film state, and when the image feature amount on a wet road surface is larger than the image feature amount on a dry, snowy road surface, the road surface does not correspond to either the wet state or the road surface state, and is measured in advance. A road surface condition determination apparatus , wherein when the road surface is larger than a threshold value that is an image feature amount on a dry road surface, the road surface is determined to be in a dry state when the road surface does not correspond to either the snowy state or the road surface state .
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