Frontal License Plate detection without deep-learning

samples/license_plate_detection.c

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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;
+}