Image location identification apparatus

Abstract: An image location identification apparatus extracts a first set of control point data for calculating transformation coefficient and a second set of control point data for verifying the transformation coefficient from image data. According to global location data entered with the image data, a map corresponding to the image data is retrieved from the map data base. A first part of the control point data for calculating transformation coefficient is selected from predetermined control points of the map and all permutations of the first part of the control point data are formed. Then, the transformation coefficients are calculated according to the first set of control point data of the image data and each permutation of the first part of the control point data of the map. The transformation coefficients are verified by using the second part of the control point data of the map. Therefore, according to the verification result, the image data matched with the map is displayed automatically and exactly.

Description: The present invention relates to an image location identification apparatus for matching image data taken by an imaging televion camera (ITV) with a corresponding map stored on a data base. When an urban area is monitored using ITV located in a helicopter, it is necessary for captured image data to be matched with a corresponding map, which may represent administrative district data or road data, on a display. For example, when a fire breaks out, a fire spot is taken by ITV from the sky. The image data and its global location data (latitude, longitude and angle of direction of view) are sent to a host computer where a map corresponding to the image data is retrieved from a map data base, according to the global location data. The image data is matched with the map, which includes houses, buildings and road data, on display. Therefore, according to the outbreak point of a fire, the path of a fire after a prescribed time can be simulated on the map. Then, against the path simulation, lead way and refuge places for inhabitants are determined. In such a case, because the image data is matched with the map by using only the global location data, an error of several hundred metres may occur between the image data and the map, which are matched on the display. Therefore, if exact location identification is necessary for the image data and the map, the user must designate control points on the image data and the map for geometrical correction. However, because image data are sent momentarily, the designation of control points by interactive mode is troublesome for the user. Furthermore, if the user is not familiar with the neighbourhood, he cannot rapidly designate control points on the display. IEEE International Conference on Robotics and Automation, 1987, vol. 3, pages 2033-2038 describes analysis of point feature representation of a perspective image. The positions of three model points u,v,w are specified in the model coordinate system. The corresponding points u",v",w" on the image plane are calculated by projecting a ray from the camera focal point. (The camera coordinate system is centered at the camera focal point). In this way, it is possible to calculate the set of transforms capable of mapping the model points into the image points according to the camera focal point (the orientation of the camera coordinate system). To verify a model hypothesis, the object features which should be visible are compared to image feature positioned near the projected location of the object feature given the hypothesised image transform. Accordingly, it is an object of the present invention to provide an image location identification apparatus, comprising: image input means for entering image data and corresponding global location data; map memory means for storing a plurality of maps, each map having global location data and control point data; retrieval means for retrieving from the map memory means, a stored map whose global location data coincide with the global location data of the image data; extract means for extracting from the image data, a first set of at least four control point data for calculating a transformation coefficient and a second set of other control point data for verifying the transformation coefficient; calculation means for selecting a first part of at least four control point data from the control point data of the map retrieved by the retrieving means, for forming all permutations of the first part of the control point data of the map, for calculating the transformation coefficient between the image data and the map, by using the first set of the control point data of the image data and the first part of the control point data for each permutation of the map, and for calculating coordinate point data corresponding to the second set of other control point data of the image data by using the transformation coefficient; verification means for determining that the transformation coefficient is correct in case that the coordinate point data are respectively situated within a predetermined limit of a second part of the control point data of the map, and in which when the coordinate point data for each permutation of the first part of the control point data are not situated within the predetermined limit of the second part of the control point data, the calculation means selects different first part of the control point data from the map, forms all permutations of the different first part of the control point data of the map, calculates transformation coefficient between the image data and the map, by using the first set of the control point data of the image data and the different first part of the control point data for each permutation of the map, and calculates another coordinate point data corresponding to the second set of the control point data of the image data by using another transformation coefficient until other coordinate point data are respectively situated within the predetermined limit of different second part of the control point data of the map. In order that the invention may be more readily understood, it will now be described, by way of example only, with reference to the accompanying drawings, in which:- Figure 1 shows schematically an image location identification apparatus of the present invention; Figure 2 shows a flow chart of the process for identifying image location according to the present invention; Figure 3 shows an example of the map area corresponding to the image data; Figure 4 shows an explanatory example of the formula of co-ordinate transformation used for identifying location between the image data and the map; Figure 5 shows an example of control points of the image data; and Figure 6 shows an example of predetermined control points of the map. Figure 1 shows the construction of an image location identification apparatus according to the present invention. Image data 1 is a video signal which is taken by an ITV mounted in a helicopter. Image processing section 2 quantize 512 x 512 pixels for the image data 1 and stores them. Then the section 2 extracts control points for location identification from quantized image data under the control of CPU 5. Location information 4 is global location, such as latitude, longitude and height, measured by the global positioning system or inertial navigation system of the helicopter. The location information 4 also includes camera parameters, such as direction and angle of view. Map data base 6 comprises memorized maps of the area being monitored which have global location data in the form of latitude and longitude for retrieval. Each map also includes data of roads, buildings, houses and many control points for location identification. CPU 5 controls all the other sections 1, 2, 3, 4, 6 and retrieves a map corresponding to the image data 1 from the map data base 6, according to the location information 4. Then CPU 5 identifies the location between the image data 1 and the retrieved map, according to predetermined control points of the retrieved map and control points of the image data extracted by the image processing section 2. Lastly, CPU 5 makes the image data 1 match with the map on display section 3. Figure 2 shows a flow chart of the process for identifying image location. Firstly, image data 1 is quantized and stored in the image processing section 2 (step 201). Next, according to the location information 4, a map area corresponding approximately to the image data 1 is determined and the map is retrieved, having area to spare (for example, 200 m extra width at the top and bottom and left and right sides (step 202, 203). The calculation of map area of map data base 6 will be explained, assuming that the latitude, longitude and height of the image taking position are X, Y Z. Furthermore, α and β represent the visual field angle directions of the camera. Secondly, area 12 which includes an admissible error limit against the area 11 is calculated. Finally, area 13 is the area 12 rotated in the direction of the angle obtained from the direction data. Next, as control points for location identification, intersections of main roads are extracted (step 204). The colour and shape of roads are different from those of buildings, parks, or green zones, and so on. Therefore, the roads as regions having a character of a predetermined colour and figure is extracted. Then the central line of each road is extracted as a control point. In this case, it is not necessary for all road regions and all cross points to be extracted, and a minimum of road regions and cross points for location identification may be extracted. Co-ordinate transformation for location identification is represented as a quadratic formula of projection transformation, assuming that the control points are situated on same plane. Namely, if a narrow area is taken by ITV, the ground surface can be regarded as a flat plane. Therefore, as shown in Figure 4, assuming that image data plane taken by ITV is L and retrieval map plane is L', point (X', Y') on the plane L' corresponding to projection central point (X, Y) on the plane L is calculated by using the following formula: X' = (b1X + b2Y = b3) / (b7X + b8Y + 1) Y' = (b4X + b5Y + b6) / (b7X + b8Y + 1). Coefficients b1 - b8 of above transformation formula are calculated by providing at least four control points corresponding to image data 1 and retrieval map data. In Figure 4, four control points of image data L are A, B, C, D and four control points of retrieval map L' are A', B', C', D'. In this place, as shown in Figure 5, assume that eleven control points are extracted in image data 1. From the eleven control points, four control points which are distributed over the image data 1 are extracted as the control points for calculating transformation coefficients. In Figure 5, four control points (2, 4, 8, 11), from which the sum of mutual distance among the four control points is a maximum, are the ones to be used for calculating the transformation coefficients and other seven control points (1, 3, 5, 6, 7, 9, 10) are the ones for verifying the transformation coefficients. As shown in Figure 6, twenty three control points have been registered in advance on the retrieval map. From the control points (1 - 23), four control points are selected in order (step 205) and all permutations of the selected four control points are formed. The procedure sequentially calculates the transformation coefficients with respect to all the possible combinations of the reference points on the image data for calculating the coefficients and any four reference points of the twenty three reference points (1 - 23) on the map data (step 205, step 206 and step 207). The procedure calculates the co-ordinates of the reference points for verification on the map data by use of the thus calculated transformation coefficients. Further the procedure judges the authenticity of the transformation coefficients by verifying whether or not the reference points of the map data are present in the vicinity of their corresponding positions (step 208). As for the first permutation (step 206), transformation coefficients between co-ordinate systems of the image data and the map are calculated by using four control points (2, 4, 8, 11) of the image data and the first permutation of selected four control points of the map (step 207). Then, by using the transformation coefficient, a co-ordinate point corresponding to the other control points (1, 3, 5, 6, 7, 9, 10) of the image data is calculated on the map and it is determined whether the predetermined control point is situated near the co-ordinate point on the map (step 208). If the predetermined controls points are situated near all of the co-ordinate points on the map, respectively, the transformation coefficient is correct (step 209). Therefore, according to the corresponding control points, the image data is matched with the map on the display section 3. However, if the predetermined control points are not situated near all of the co-ordinate points on the map, respectively, the transformation coefficient is not correct. Therefore, a second permutation of the selected four control points, using the above-mentioned processing (step 207, 208, 209) is repeated (step 210). If the transformation coefficient is not correct as for all permutations of the selected four points, another four control points are selected from the control points (1 - 23) in the map (step 211). As for the second selected four control points, the above-mentioned processing (step 206, 207, 208, 209, 210) is repeated. This process is repeated until a correct transformation coefficient is found with a different four control points selected, in turn, and the above-mentioned processing being repeated. In Figure 6, first four control points (1, 2, 3, 4) are selected from predetermined control points (1 - 23). All permutation of the first four control points are (1, 2, 3, 4), (1, 2, 4, 3), (1, 3, 2, 4), (1, 3, 4, 2), (1, 4, 2, 3), (1, 4, 3, 2,), (2, 1, 3, 4), (2, 1, 4, 3), (2, 3, 1, 4), (2, 3, 4, 1), (2, 4, 1, 3), (2, 4, 3, 1), (3, 1, 2, 4), (3, 1, 4, 2,), (3, 2, 1, 4), (3, 2, 4, 1), (3, 4, 1, 2), (3, 4, 2, 1), (4, 1, 2, 3), (4, 1, 3, 2), (4, 2, 1, 3), (4, 2, 3, 1), (4, 3, 1, 2), (4, 3, 2, 1). Then, transformation coefficients between each permutation and the four control points (2, 4, 8, 11) of the image data (as shown in Figure 5) are calculated, taking account of the control points order. In this case, since each transformation coefficient of all permutations is not correct, the second four control points (1, 2, 3, 5) are selected from predetermined control points (1 - 23) of the map, and all permutations of the second four control points (1, 2, 3, 5) are formed and each transformation coefficient is calculated for all permutations. In this way, when the same permutation of four control points (6, 8, 15, 18) from the map (as shown in Figure 6) is selected, the transformation coefficient is correct. In short, the transformation coefficient between four control points (6, 8, 15, 18) on the map and four control points (2, 4, 8, 11) on the image data is calculated. According to this transformation coefficient, co-ordinate points corresponding to control points (1, 3, 5, 6, 7, 9, 10) for verifying on the image data are situated just as predetermined control points (5, 7, 10, 11, 12, 16, 17) on the map. Lastly, by using corresponding control points between the image data and the map, the image data is matched with the map automatically and the image data and the map, when they are matched, are displayed on the display section 3.

Claims: An image location identification apparatus, comprising: image input means (1,4) for entering image data and corresponding global location data; map memory means (6) for storing a plurality of maps, each map having global location data and control point data; retrieval means (5) for retrieving from the map memory means, a stored map whose global location data coincide with the global location data of the image data; extract means (2) for extracting from the image data, a first set of at least four control point data for calculating a transformation coefficient and a second set of other control point data for verifying the transformation coefficient; calculation means (5) for selecting a first part of at least four control point data from the control point data of the map retrieved by the retrieving means (5), for forming all permutations of the first part of the control point data of the map, for calculating the transformation coefficient between the image data and the map, by using the first set of the control point data of the image data and the first part of the control point data for each permutation of the map, and for calculating coordinate point data corresponding to the second set of other control point data of the image data by using the transformation coefficient; verification means (5) for determining that the transformation coefficient is correct in case that the coordinate point data are respectively situated within a predetermined limit of a second part of the control point data of the map, and in which when the coordinate point data for each permutation of the first part of the control point data are not situated within the predetermined limit of the second part of the control point data, the calculation means (5) selects different first part of the control point data from the map, forms all permutations of the different first part of the control point data of the map, calculates transformation coefficient between the image data and the map, by using the first set of the control point data of the image data and the different first part of the control point data for each permutation of the map, and calculates another coordinate point data corresponding to the second set of the control point data of the image data by using another transformation coefficient until other coordinate point data are respectively situated within the predetermined limit of different second part of the control point data of the map. The image location identification apparatus according to claim 1, wherein the global location data are latitude, longitude, height and angle of direction of view. The image location identification apparatus according to claim 1 or 2, wherein the retrieval means retrieves a map whose area includes the image data area and additional area sufficiently to overcome global location data error. The image location identification apparatus to any preceding claim, further including display means (3) for displaying the image data which is matched with the map, when the condition for the co-ordinate point data is satisfied. The image location identification apparatus according to claim 1, wherein the first set of control point data are selected so that the sum of the mutual distance among the four control points is a maximum. A method of identifying image location comprising the steps of: entering image data and corresponding global location data; memorising a plurality of maps, with each map having global location data and control point data; retrieving from the plurality of maps, a memorised map whose global location data coincide with the global location data of the image data; extracting from the image data, a first set of at least four control point data for calculating a transformation coefficient and a second set of other control point data for verifying the transformation coefficient; selecting a first part of at least four control point data from the control point data of the map at the retrieving step; forming all permutations of the first part of the control point data of the map; calculating the transformation coefficient between the image data and the map by using the first set of the control point data of the image data and the first part of the control point data for each permutation of the map; calculating coordinate point data corresponding to the second set of other control point data of the image by using the transformation coefficient; determining that the transformation coefficient is correct in case that the coordinate point data are respectively situated within a predetermined limit of a second part of the control point data of the map, selecting different first part of the control point data from the map, when the coordinate point data for each permutation of the first part of the control point data are not situated within the predetermined limit of the second part of the control point data; forming all permutations of the different first part of the control point data of the map; calculating transformation coefficient between the image data and the map by using the first set of the control point data of the image data and the different first part of the control point data for each permutation of the map; and calculating another coordinate point data corresponding to the second set of the control point data of the image data by using another transformation coefficient, until other coordinate point data are respectively situated with the predetermined limit of different second part of the control point data of the map. The method of identifying image location according to claim 6, wherein the global location data are latitude, longitude, height and angle direction of view. The method of identifying image location according to claim 7, wherein, at the retrieving step, a map area includes the image data area and additional area sufficient to overcome global location data error. The method of identifying image location according to claim 8, further comprising the step of displaying the image data which is matched with the map when the condition for the co-ordinate point data is satisfied. The method of identifying image location according to claim 6, wherein the first set of control point data are selected so that the sum of the mutual distance among the four control points is a maximum.

Inventors: NUMAGAMI HIDEO, NUMAGAMI, HIDEO
Applicants: TOSHIBA KK, KABUSHIKI KAISHA TOSHIBA
Application year: 1990
Main classification: G06K9
IPC codes: G06T11, G06K9, G06T7, G06T3, G06F17