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April 1, 2018 03:33
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Frontal License Plate detection without deep-learning. Only image processing code - https://sod.pixlab.io
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/* | |
* Programming introduction with the SOD Embedded Image Processing API. | |
* Copyright (C) PixLab | Symisc Systems, https://sod.pixlab.io | |
*/ | |
/* | |
* Compile this file together with the SOD embedded source code to generate | |
* the executable. For example: | |
* | |
* gcc sod.c license_plate_detection.c -lm -Ofast -march=native -Wall -std=c99 -o sod_img_proc | |
* | |
* Under Microsoft Visual Studio (>= 2015), just drop `sod.c` and its accompanying | |
* header files on your source tree and you're done. If you have any trouble | |
* integrating SOD in your project, please submit a support request at: | |
* https://sod.pixlab.io/support.html | |
*/ | |
/* | |
* This simple program is a quick introduction on how to embed and start | |
* experimenting with SOD without having to do a lot of tedious | |
* reading and configuration. | |
* | |
* Make sure you have the latest release of SOD from: | |
* https://pixlab.io/downloads | |
* The SOD Embedded C/C++ documentation is available at: | |
* https://sod.pixlab.io/api.html | |
*/ | |
#include <stdio.h> | |
#include "sod.h" | |
/* | |
* Frontal License Plate detection without deep-learning. Only image processing code. | |
*/ | |
static int filter_cb(int width, int height) | |
{ | |
/* A filter callback invoked by the blob routine each time | |
* a potential blob region is identified. | |
* We use the `width` and `height` parameters supplied | |
* to discard regions of non interest (i.e. too big or too small). | |
*/ | |
if ((width > 300 && height > 200) || width < 45 || height < 45) { | |
/* Ignore small or big boxes (You should take in consideration | |
* U.S plate size here and adjust accordingly). | |
*/ | |
return 0; /* Discarded region */ | |
} | |
return 1; /* Accepted region */ | |
} | |
int main(int argc, char *argv[]) | |
{ | |
/* Input image (pass a path or use the test image shipped with the samples ZIP archive) */ | |
const char *zInput = argc > 1 ? argv[1] : "./plate.jpg"; | |
/* Processed output image path */ | |
const char *zOut = argc > 2 ? argv[2] : "./out_plate.png"; | |
/* Load the input image in the grayscale colorspace */ | |
sod_img imgIn = sod_img_load_grayscale(zInput); | |
if (imgIn.data == 0) { | |
/* Invalid path, unsupported format, memory failure, etc. */ | |
puts("Cannot load input image..exiting"); | |
return 0; | |
} | |
/* A full color copy of the input image so we can draw rose boxes | |
* marking the plate in question if any. | |
*/ | |
sod_img imgCopy = sod_img_load_color(zInput); | |
/* Obtain a binary image first */ | |
sod_img binImg = sod_threshold_image(imgIn, 0.5); | |
/* | |
* Perform Canny edge detection next which is a mandatory step | |
*/ | |
sod_img cannyImg = sod_canny_edge_image(binImg, 1/* Reduce noise */); | |
/* | |
* Dilate the image say 12 times but you should experiment | |
* with different values for best results which depend | |
* on the quality of the input image/frame. */ | |
sod_img dilImg = sod_dilate_image(cannyImg, 12); | |
/* Perform connected component labeling or blob detection | |
* now on the binary, canny edged, Gaussian noise reduced and | |
* finally dilated image using our filter callback that should | |
* discard small or large rectangle areas. | |
*/ | |
sod_box *box = 0; | |
int i, nbox; | |
sod_image_find_blobs(dilImg, &box, &nbox, filter_cb); | |
/* Draw a box on each potential plate coordinates */ | |
for (i = 0; i < nbox; i++) { | |
sod_image_draw_bbox_width(imgCopy, box[i], 5, 255., 0, 225.); // rose box | |
} | |
sod_image_blob_boxes_release(box); | |
/* Finally save the output image to the specified path */ | |
sod_img_save_as_png(imgCopy, zOut); | |
/* Cleanup */ | |
sod_free_image(imgIn); | |
sod_free_image(cannyImg); | |
sod_free_image(binImg); | |
sod_free_image(dilImg); | |
sod_free_image(imgCopy); | |
return 0; | |
} |
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Frontal License Plate detection without deep-learning. Only image processing code
SOD Embedded Homepage: https://sod.pixlab.io
SOD C/C++ API documentation: https://sod.pixlab.io/api.html
Getting Started with SOD Embedded: https://sod.pixlab.io/intro.html