Added two new configuration options to control detection.

Enforcing a maximum resolution for the image input to detection
Adding a configurable "strictness" to tighten or loosen the detection leniency

config/openalpr.conf

@@ -7,16 +7,30 @@ runtime_dir = /usr/share/openalpr/runtime_data
 ocr_img_size_percent = 1.33333333
 state_id_img_size_percent = 2.0
 
+; detection will ignore plates that are too large.  This is a good efficiency technique to use if the 
+; plates are going to be a fixed distance away from the camera (e.g., you will never see plates that fill 
+; up the entire image
 max_plate_width_percent = 100
 max_plate_height_percent = 100
 
-
 ; detection_iteration_increase is the percentage that the LBP frame increases each iteration.
 ; It must be greater than 1.0.  A value of 1.01 means increase by 1%, 1.10 increases it by 10% each time. 
 ; So a 1% increase would be ~10x slower than 10% to process, but it has a higher chance of landing 
 ; directly on the plate and getting a strong detection
 detection_iteration_increase = 1.1
 
+; The minimum detection strength determines how sure the detection algorithm must be before signaling that 
+; a plate region exists.  Technically this corresponds to LBP nearest neighbors (e.g., how many detections 
+; are clustered around the same area).  For example, 2 = very lenient, 9 = very strict.
+detection_strictness = 3
+
+; The detection doesn't necessarily need an extremely high resolution image in order to detect plates
+; Using a smaller input image should still find the plates and will do it faster
+; Tweaking the max_detection_input values will resize the input image if it is larger than these sizes 
+; max_detection_input_width/height are specified in pixels
+max_detection_input_width = 1280
+max_detection_input_height = 720
+
 opencl_enabled = 0
 multithreading_cores = 1
 

src/openalpr/config.cpp

@@ -118,8 +118,11 @@ void Config::loadValues(string country)
   multithreading_cores = getInt("common", "multithreading_cores", 1);
 
   detection_iteration_increase = getFloat("common", "detection_iteration_increase", 1.1);
+  detectionStrictness = getInt("common", "detection_strictness", 3);
   maxPlateWidthPercent = getFloat("common", "max_plate_width_percent", 100);
   maxPlateHeightPercent = getFloat("common", "max_plate_height_percent", 100);
+  maxDetectionInputWidth = getInt("common", "max_detection_input_width", 1280);
+  maxDetectionInputHeight = getInt("common", "max_detection_input_height", 768);
 
   maxPlateAngleDegrees = getInt("common", "max_plate_angle_degrees", 15);
   

src/openalpr/config.h

@@ -48,8 +48,11 @@ class Config
     int multithreading_cores;
     
     float detection_iteration_increase;
+    int detectionStrictness;
     float maxPlateWidthPercent;
     float maxPlateHeightPercent;
+    int maxDetectionInputWidth;
+    int maxDetectionInputHeight;
     
     int maxPlateAngleDegrees;
     

src/openalpr/regiondetector.cpp

@@ -25,7 +25,6 @@ using namespace std;
 RegionDetector::RegionDetector(Config* config)
 {
   this->config = config;
-  // Don't scale.  Can change this in the future (i.e., maximum resolution preference, or some such).
   this->scale_factor = 1.0f;
 
   // Load either the regular or OpenCL version of the cascade classifier
@@ -68,7 +67,25 @@ vector<PlateRegion> RegionDetector::detect(Mat frame)
 /** @function detectAndDisplay */
 vector<PlateRegion> RegionDetector::doCascade(Mat frame)
 {
-  //float scale_factor = 1;
+
+  
+  if (frame.cols > config->maxDetectionInputWidth)
+  {
+    // The frame is too wide
+    this->scale_factor = ((float) config->maxDetectionInputWidth) / ((float) frame.cols);
+    
+    if (config->debugGeneral)
+      std::cout << "Input detection image is too wide.  Resizing with scale: " << this->scale_factor << endl;
+  }
+  else if (frame.rows > config->maxDetectionInputHeight)
+  {
+    // The frame is too tall
+    this->scale_factor = ((float) config->maxDetectionInputHeight) / ((float) frame.rows);
+    
+    if (config->debugGeneral)
+      std::cout << "Input detection image is too tall.  Resizing with scale: " << this->scale_factor << endl;
+  }
+  
   int w = frame.size().width;
   int h = frame.size().height;
 
@@ -84,8 +101,7 @@ vector<PlateRegion> RegionDetector::doCascade(Mat frame)
   Size minSize(config->minPlateSizeWidthPx * this->scale_factor, config->minPlateSizeHeightPx * this->scale_factor);
   Size maxSize(w * config->maxPlateWidthPercent * this->scale_factor, h * config->maxPlateHeightPercent * this->scale_factor);
 
-
-  plate_cascade->detectMultiScale( frame, plates, config->detection_iteration_increase, 3,
+  plate_cascade->detectMultiScale( frame, plates, config->detection_iteration_increase, config->detectionStrictness,
 				    0,
 				    //0|CV_HAAR_SCALE_IMAGE,
 				    minSize, maxSize );