CN110555389B - Bullet line-bore trace identification method based on ridgelet transformation and rotation matching - Google Patents
Bullet line-bore trace identification method based on ridgelet transformation and rotation matching Download PDFInfo
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Abstract
The invention discloses a bullet line-bore trace identification method based on ridgelet transformation and rotation matching, which comprises the following steps: acquiring bullet thread chamber trace data by using a three-dimensional confocal microscope; filtering the acquired chamber trace by adopting a low-pass spline filter to obtain rough texture on the surface of the bullet; carrying out finite ridge wave transformation on the line chamber trace, carrying out maximum value detection, and carrying out finite ridge wave inverse transformation on a detection result to reconstruct the line chamber line trace; measuring the inclination angle of the linear trace image through Rodan transformation and correcting; calculating the mean value of each row of the image, and homogenizing the outline curve of the line chamber trace; calculating the cross-correlation value of the contour curve of the trace of the line chamber, calculating the standard deviation and the peak value of the cross-correlation value, calculating the prominent multiple of the peak value, extracting the maximum value of the peak value and the prominent multiple, comparing, and judging whether the bullets are matched. The bullet linehole trace identification method based on the ridgelet transformation and the rotation matching can not only realize the rapid extraction of the bullet linehole trace, but also carry out the rapid rotation matching of the trace to be matched and the known trace, and can provide clues for case solving and litigation evidences for the case involving the gun.
Description
Technical Field
The invention relates to the field of bullet trace identification and identification, in particular to a bullet line bore trace identification method based on ridgelet transformation and rotation matching.
Background
The rifling of the barrel leaves scratch marks on the bullet after the bullet is shot, and the rifling, the abrasion degree and the surface characteristics of the rifling of each barrel are different, so that the scratches formed on the surface of the bullet after the bullet is shot from the barrel are also different. Thus, by comparing the line-bore scratches on the bullet, the matching and source finding of the bullet can be achieved. Therefore, powerful evidence is provided for the police to detect the gun-related case. Generally, in the traditional bullet surface trace identification, manual comparison is carried out by observing the trace shape of a bullet by using a microscope, so that the time consumption is long, the workload is large, the efficiency is low, the subjective influence of people is large, the comparison of the bullet surface trace is very difficult, and the difficulty is increased for treating gun-related cases.
With the development of computer information processing technology, the application of computer information processing technology to trace detection and identification is rapidly developed. All countries in the world are dedicated to researching the automatic bullet mark recognition system, and the system has very good effect, such as IBIS, EVOFINDER, BALSCAN, ALIAS and the like. The acquisition of bullet surface traces by using a three-dimensional confocal microscope has become a mainstream technology. Most scratches on the surface of the bullet are linear stripes, and the ridge wave can solve the singularity of linear and super-planar shapes and solve the problem that the image edge is expressed under the two-dimensional condition. The ridge wave transformation is to convert the linear singularities in different directions into point singularities by utilizing Randon transformation, and the wavelet transformation has a very excellent effect on processing the point singularities, so that the wavelet transformation is utilized to process, and the effective representation of the linear characteristics in the image is realized. Therefore, accurate extraction of linear streaks can be achieved using finite ridgelet transformation. The application of the ridgelet transformation to the extraction and identification of the bullet line-bore linear trace based on the theory has high feasibility.
Disclosure of Invention
The invention provides a bullet line-bore trace identification method based on ridgelet transformation and rotation matching, which can realize extraction and comparison of bullet line-bore traces and realize rotation matching of bullet line-bore traces.
In order to solve the technical problems, the invention adopts a technical scheme that: the warhead line-bore trace identification method based on ridge wave transformation and rotation matching is characterized by comprising the following steps of:
a bullet line-bore trace identification method based on ridgelet transformation and rotation matching comprises the following steps:
step (1): acquiring bullet thread chamber trace data by using a three-dimensional confocal microscope and preprocessing the bullet thread chamber trace data;
step (2): carrying out limited ridgelet transformation on the bullet chamber trace image preprocessed in the step (1), and carrying out maximum value detection; then, obtaining a reconstructed image by utilizing finite ridge wave inverse transformation, and finishing the extraction of the linear trace of the line chamber;
and (3): measuring an inclination angle by utilizing Radon transformation according to the reconstructed image in the step (2) and correcting to obtain a corrected image;
and (4): obtaining an average value and a homogenizing profile curve of the bullet chamber trace along the column vector according to the corrected image in the step (3);
and (5): and (4) performing cross-correlation calculation on the homogenized profile curve obtained in the step (4), and rotating and matching the trace number corresponding to the maximum peak value and the maximum protruding multiple of the cross-correlation value to realize the matching of the trace of the bullet chamber.
The specific steps of the step (1) are as follows:
1) acquiring bullet thread chamber trace data by using a three-dimensional confocal microscope;
2) using a spline filter to perform low-pass filtering on data of bullet chamber traces collected by a three-dimensional confocal microscope, wherein the wavelength is 40-100 mu m;
3) and (4) performing difference on the bullet bore trace data before filtering and the low-pass filtered data to obtain trace texture left on the bullet by rifling.
The specific steps of the step (2) are as follows:
1) dividing the bullet line chamber trace image into sub-images with the size of P multiplied by P, wherein P is a prime number;
2) subtracting the mean value of the image to realize zero mean value operation before finite Radon transformation;
3) carrying out finite Radon transformation on the image with the average value subtracted, converting linear singularity into point singularity, and obtaining a coefficient matrix with the size of (P multiplied by P + 1);
4) each row of the image after the limited Radon transformation is subjected to one-dimensional wavelet decomposition, DB4 wavelets are subjected to 5 layers of decomposition layers, the signal continuation mode is periodic continuation, and limited ridgelet transformation is realized;
5) and (3) performing modulus maximum value detection on the vector after wavelet transformation, and performing limited ridge wave inverse transformation on the detection result to realize image reconstruction and accurate extraction of bullet chamber trace stripes.
The specific steps of the step (3) are as follows:
1) removing discrete noise points from the image by using a two-dimensional wiener filter function;
2) the edge is detected through an edge detection canny operator, so that the interference is reduced;
3) radon transformation is carried out along the angle of the projection direction, each point of the transformed matrix R is the line integral of the original matrix, and each projection direction corresponds to a column vector;
4) searching the position of the maximum value in the matrix R, extracting row and column marks, finding out the maximum projection angle corresponding to each angle, and taking the maximum value to obtain the maximum inclination angle;
5) and inputting the inclination angle into a rotating image command function to realize image rectification.
The specific steps of the step (4) are as follows:
and calculating the average value of the stripes of the corrected image along each row by using an averaging command function mean, namely normalizing the effective stripe area to form a two-dimensional bullet chamber trace contour line. Wherein computing the average of the fringes effectively removes the interference of random textures.
The specific steps of the step (5) are as follows:
1) sequentially taking out the contour curves of the line chamber traces of the bullets to be matched according to the rotation sequence, and respectively adopting a rotation calculation mode
Performing cross-correlation calculation with the line chamber contour line of the known bullet;
2) extracting the peak value of each group of cross-correlation values and the maximum value of each round of peak values;
3) calculating the standard deviation and the mean value of the cross-correlation values of each group;
4) calculate the prominent multiple of the peak: (peak-to-mean)/standard deviation;
5) detecting the rotation sequence corresponding to the maximum value of the peak value and the maximum value of the peak value projection multiple, and continuously matching the rotation sequence
Matching the maximum value and the number of the protruding times, and determining the bullet matching and the bullet homology.
The invention has the beneficial effects that: the bullet line-bore trace identification method based on ridgelet transformation and rotation matching not only can realize extraction of a large number of bullet line-bore traces, but also can realize matching judgment of the bullet line-bore traces, and can provide case-solving clues and litigation evidence for cases involved in guns.
Drawings
FIG. 1 is a flow chart of a bullet line-bore trace identification method based on ridgelet transformation and rotation matching according to the invention;
FIG. 2a is a schematic diagram of a bullet line-bore trace acquired by a three-dimensional confocal microscope in the bullet line-bore trace identification method based on ridgelet transformation and rotation matching according to the present invention;
FIG. 2b is a schematic diagram of the warhead line-bore trace identification method based on ridge wave transformation and rotation matching after being filtered by a low-pass spline filter;
FIG. 3 is a schematic diagram of the bullet line-bore trace identification method based on ridgelet transformation and rotation matching after limited ridgelet transformation and processing;
FIG. 4 is a schematic diagram of the bullet line-bore trace identification method based on ridgelet transformation and rotation matching after image correction;
fig. 5 is a diagram illustrating a homogenized profile curve and a cross-correlation value curve of the bullet line bore trace in the bullet line bore trace identification method based on ridgelet transformation and rotation matching.
Detailed Description
The embodiments of the present invention will be described in detail with reference to the accompanying drawings so that the advantages and features of the invention can be more easily understood by those skilled in the art, and the scope of the invention will be clearly and clearly defined.
As shown in the figures 1 to 5 of the drawings,
referring to fig. 1, the present invention provides a bullet chamber trace identification method based on ridgelet transformation and rotation matching, including the steps of:
step (1): the method comprises the following steps of collecting bullet thread chamber trace data by using a three-dimensional confocal microscope and preprocessing the bullet thread chamber trace data, wherein the method comprises the following specific steps:
1) acquiring bullet line-bore trace data by using a three-dimensional confocal microscope, wherein a figure 2a shows a line-bore trace image acquired by the three-dimensional confocal microscope, and the line-bore trace cannot be distinguished from the image by naked eyes;
2) using a spline filter to perform low-pass filtering on data of bullet chamber traces collected by a three-dimensional confocal microscope, wherein the wavelength is 80 mu m;
3) the bullet line bore trace data before filtering and the low-pass filtered data are subjected to subtraction, the result is trace texture left on the bullet by rifling, and fig. 2b is a filtered trace image, so that the line bore trace texture can be clearly seen after the image is subjected to low-pass filtering;
step (2): and (3) carrying out limited ridgelet transformation on the preprocessed image and processing the reconstructed image, wherein the specific steps are as follows:
1) decomposing the bullet line bore trace image into a plurality of sub-images with the size of 257 multiplied by 257;
2) subtracting the mean value of the image to realize zero mean value operation before finite Radon transformation;
3) carrying out finite Radon transformation on the image with the average value subtracted, converting the linear singularity into the point singularity, and obtaining a coefficient matrix with the size of (257 multiplied by 257+ 1);
4) each column of the image after the limited Radon transformation is subjected to one-dimensional wavelet decomposition, DB4 wavelets and5 decomposition layers are adopted, the signal continuation mode is periodic continuation, and limited ridgelet transformation is realized;
5) the vector after wavelet transformation is subjected to modulus maximum value detection, the detection result is subjected to limited ridgelet inverse transformation, namely, the accurate extraction of the reconstructed bullet line-chamber trace stripes of the image is realized, and fig. 3 is an image reconstructed after limited ridgelet transformation, extreme value detection processing and limited ridgelet inverse transformation, each line trace can be clearly seen from the image, so that much interference is removed, and the effect of extracting the line stripes by the limited ridgelet transformation is very good.
And (3): the method comprises the following steps of utilizing Radon transformation to realize inclination angle measurement and image rectification, and specifically comprising the following steps:
1) removing discrete noise points from the image by using a two-dimensional wiener filter function;
2) the edge is detected through an edge detection canny operator, so that the interference is reduced;
3) radon transformation is carried out along the angle of the projection direction, each point of the transformed matrix R is the line integral of the original matrix, and each projection direction corresponds to a column vector;
4) searching the position of the maximum value in the matrix R, extracting row and column marks, finding out the maximum projection angle corresponding to each angle, and taking the maximum value to obtain the maximum inclination angle;
5) inputting the inclination angle into a rotating image command function, wherein a corrected image is shown in FIG. 4, and the corrected image is beneficial to removing random textures and solving a trace homogenizing contour curve;
and (4): averaging according to the columns to obtain a homogenization profile curve of the bullet chamber scratch, and specifically comprising the following steps:
and calculating the average value of the stripes of the corrected image along each row by using an averaging command function mean, namely normalizing the effective stripe area into a two-dimensional bullet chamber trace contour line. Figure 5 is a homogenized contour line of a bullet chamber trace. Wherein computing the average of the fringes effectively removes the interference of random textures.
(5) According to the obtained homogenized profile curve, performing cross-correlation calculation, and rotationally matching the trace number corresponding to the maximum peak value and the maximum protruding multiple of the cross-correlation value to realize the matching of the trace of the bullet chamber, wherein the method comprises the following specific steps:
1) the bullets to be matched are recorded as brA1, the marks of the thread chamber are respectively recorded as brA1land1, brA1land2, brA1land3, br A1land4, brA1land5 and brA1land6, the known bullet is br11, and the corresponding bullet marks are br11land1, br11land2, br11land3, br11land4, br11land5 and br11land 6. Taking out the contour curve of the first bullet trace brA1land1 to be matched and the contour curve of the trace of the known bullet, and performing cross-correlation calculation respectively by br11 land1-br11 land6 according to the rotating sequence;
2) extracting peak values of each group of cross-correlation values and the maximum value of each round of peak values, wherein the peak values of each round of cross-correlation values are shown in table 1, and the maximum peak values are 0.66165, 0.76712, 0.77488, 0.83436, 0.74570 and 0.64581 respectively;
3) calculating the standard deviation and the mean value of the cross-correlation values of each group;
4) calculate the prominent multiple of the peak: (peak-mean)/standard deviation, extract the maximum value of the fold of prominence for each round. Table 2 shows the projection multiple of the peak value of each round, and the maximum projection multiple is 3.31088, 6.10245, 7.40159, 7.09223, 2.38422 and 3.89805 respectively;
5) the rotation sequence corresponding to the maximum value of the peak value and the maximum value of the peak protrusion multiple is detected, the sequence numbers corresponding to one rotation of the maximum peak value of each group in the table 1 and the table 2 are respectively 1 land-br 11land, 1 land-br 11land and1 land-br 11land, and the sequence numbers corresponding to one rotation of the maximum protrusion multiple are respectively 1 land-br 11land, and1 land-br 11 land. The corresponding numbers have certain rotation sequence, which shows that the numbers of all the line-chamber traces of the bullet rotating for one circle are matched with the line-chamber trace numbers of the matched bullet according to the matching sequence, so that bullet matching and homology can be judged; the sequence of the comparison of the maximum projection multiples shows that a discontinuous matching result appears in six matching line-chamber traces, but more than three continuous line-chamber traces matched according to the rotation sequence still exist in one round of bullet rotation, and the matching of two bullets can be judged by combining the sequence result matched by the maximum peak value, and the two bullets come from the same firearm. Therefore, whether the bullets are matched can be judged by the method and used as a basis for judging the bullet sources.
TABLE 1 Cross-correlation values for bullet brA1 and br11 rotational matches
TABLE 2 outstanding multiple of cross-correlation value peaks for bullet br A1 and br11 rotation matches
Aiming at the problems of complex trace, more bullet scratches, difficult manual identification and the like in bullet line chamber trace identification, the invention provides a bullet line chamber trace identification method based on ridgelet transformation and rotation matching, and comparison and judgment of bullet line chamber traces are realized.
The ridge transformation maps the line singularities in different directions into point singularities by utilizing Radon transformation, so that the effective representation of the straight line characteristics in the image is realized, and the accurate extraction of the linear characteristics can be realized by utilizing wavelet transformation with a very good effect on the point singularity processing. And reconstructing the image by utilizing inverse ridge wave transformation to realize linear extraction of the line-bore trace. And detecting the inclination angle of the linear stripe by using Ra don transformation and correcting, calculating the average value of each corrected row by using a mean function, namely the outline of the line chamber trace, performing cross-correlation calculation on the outline, calculating the standard deviation, the peak value, the average value and the peak protrusion multiple of each group of cross-correlation values, extracting the maximum peak value and the maximum protrusion multiple, and realizing the rotary matching of the line chamber trace. More than three groups of serial numbers are numbered according to the sequence of one round of bullet rotation and are according to the matched trace, so that the bullet can be identified as matched, otherwise, the bullet is not matched.
The above description is only an embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or applied directly or indirectly to other technical fields, are included in the scope of the present invention.
Claims (5)
1. A bullet line-bore trace identification method based on ridgelet transformation and rotation matching is characterized by comprising the following steps:
step (1): acquiring bullet thread chamber trace data by using a three-dimensional confocal microscope and preprocessing the bullet thread chamber trace data;
step (2): carrying out limited ridgelet transformation on the bullet chamber trace image preprocessed in the step (1), and carrying out maximum value detection; then, obtaining a reconstructed image by utilizing finite ridge wave inverse transformation, and finishing the extraction of the linear trace of the line chamber;
and (3): measuring an inclination angle by utilizing Radon transformation according to the reconstructed image in the step (2) and correcting to obtain a corrected image;
and (4): obtaining an average value and a homogenizing profile curve of the bullet chamber trace along the column vector according to the corrected image in the step (3);
and (5): performing cross-correlation calculation on the homogenized profile curve obtained in the step (4), and rotationally matching the trace number corresponding to the maximum peak value and the maximum protruding multiple of the cross-correlation value to realize the matching of the trace of the bullet chamber;
the specific steps of the step (5) are as follows:
1) sequentially taking out the contour curves of the line chamber traces of the bullets to be matched according to the rotation sequence, and respectively performing cross-correlation calculation with the line chamber contour lines of the known bullets in a rotation calculation mode;
2) extracting the peak value of each group of cross-correlation values and the maximum value of each round of peak values;
3) calculating the standard deviation and the mean value of the cross-correlation values of each group;
4) calculate the prominent multiple of the peak: (peak-to-mean)/standard deviation;
5) and detecting the rotation sequence corresponding to the maximum value of the peak value and the maximum value of the peak value projection multiple, and identifying bullet matching and homology when the maximum value and the projection multiple are continuously matched according to the rotation sequence and the number.
2. The warhead line-bore trace identification method based on ridgelet transformation and rotation matching according to claim 1, wherein the specific steps of step (1) are as follows:
1) acquiring bullet thread chamber trace data by using a three-dimensional confocal microscope;
2) using a spline filter to perform low-pass filtering on data of warhead line-bore trace acquired by a three-dimensional confocal microscope, wherein the wavelength is 40-100
；
3) And (4) performing difference on the bullet bore trace data before filtering and the low-pass filtered data to obtain trace texture left on the bullet by rifling.
3. The warhead line-bore trace identification method based on ridgelet transformation and rotation matching as claimed in claim 1, wherein the specific steps of said step (2) are as follows:
1) dividing bullet chamber trace image into
The size of the sub-image,
is a prime number;
2) subtracting the mean value of the image to realize zero mean value operation before finite Radon transformation;
3) the image with the mean value subtracted is subjected to finite Radon transformation, linear singularity is converted into point singularity, and the value is obtained
) A coefficient matrix of (a);
4) each row of the image after the limited Radon transformation is subjected to one-dimensional wavelet decomposition, DB4 wavelets are subjected to 5 layers of decomposition layers, the signal continuation mode is periodic continuation, and limited ridgelet transformation is realized;
5) and (3) performing modulus maximum value detection on the vector after wavelet transformation, and performing limited ridge wave inverse transformation on the detection result to realize image reconstruction and accurate extraction of bullet chamber trace stripes.
4. The warhead line-bore trace identification method based on ridgelet transformation and rotation matching as claimed in claim 1, wherein the specific steps of said step (3) are as follows:
1) removing discrete noise points from the image by using a two-dimensional wiener filter function;
2) edges are detected through an edge detection canny operator, so that interference is reduced;
3) radon transformation is carried out along the angle of the projection direction, and the transformed matrix
Each point of the matrix is the line integral of the original matrix, and the direction of each projection corresponds to a column vector;
4) retrieval matrix
Extracting a row and column mark at the position of the medium maximum value, finding out the maximum projection angle corresponding to each angle, and taking the maximum value of the projection angle as the maximum inclination angle;
5) and inputting the inclination angle into a rotating image command function to realize image rectification.
5. The warhead line-bore trace identification method based on ridgelet transformation and rotation matching as claimed in claim 1, wherein the specific steps of said step (4) are as follows:
calculating the average value of the stripes of the corrected image along the column direction by adopting an average value command function mean, and normalizing the effective stripe area into a two-dimensional bullet chamber trace contour line through calculation; the method for calculating the average value of the stripes effectively removes the interference of random textures.
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