ucw. docs: document single-line doc. comments

[libucw.git] / cf / images

diff --git a/cf/images b/cf/images
index b380d681614ab9f1a6b88e3114a25707b097d1a3..ab8dc24ed8c04f81efc0f87f0d8f6825e0d560cb 100644 (file)
--- a/cf/images
+++ b/cf/images
@@ -2,24 +2,51 @@
 
 ######## General parameters #####################################################
 
-Images {
+ImageLib {
+
+# Default tracing level (0 to disable)
+Trace                  0
+
+# Limits for image allocation
+ImageMaxDim            0xffff          # Maximum width/height (at most 64k-1)
+ImageMaxBytes          256M            # Maximum size in bytes
+
 }
 
+#if CONFIG_IMAGES_DUP || CONFIG_IMAGES_SIM
 ######## Image signatures #######################################################
 
 ImageSig {
 
-MinWidth       16
-MinHeight      16
+# To find similar images, Sherlock uses comparison based on regions.
+# First of all, the imagesim analyser extracts various region features.
+# Sets of these features are called "image signatures" and they are stored
+# in the `H' attribute of image objects.
+
+# Signatures are later processed by the indexer to build an effective
+# search structure finally used by the search server. See Indexer and Search
+# sections for more options.
 
+# Minimum image size to apply segmentation. Smaller images are always
+# compared by the simple "average" method (see ImageSig.CompareMethod).
+MinWidth               16
+MinHeight              16
+
+# List of subdivision thresholds in the first phase of segmentation.
+# Lower the values to increase the average number of regions and vice versa.
 PreQuantThresholds     6 12 15 20 25 25 30 30 40 40 50 50 60 60 60
+
+# Settings for the second phase of segmentation -- usually not so important.
+# We use an iterative algorithm to improve the average error from the first phase.
+# We stop the process after PostQuantMaxSteps or if we get only PostQuantThreshold
+# percentual improvement over the previous step.
 PostQuantMinSteps      2
 PostQuantMaxSteps      10
 PostQuantThreshold     1
 
 # BorderBonus and BorderSize parameters can increase or decrease the weight
 # of image pixels near the borders. Weight of all pixels more than BorderSize * MIN(cols, rows)
-# pixels far from the edges is 128. Then this value continuously decrese/increse up to 128+BorderSize.
+# pixels far from the edges is 128. Then this value continuously decreses/increses up to 128+BorderSize.
 BorderSize             0.4
 BorderBonus            -50
 
@@ -31,14 +58,14 @@ InertiaScale                2 0.5 0.05
 # set it to zero to disable the algorithm completely.
 TexturedThreshold      0.32
 
-# Signatures comparision method (integrated|fuzzy|average):
+# Signature comparison method:
 #
 #   integrated
 #      based on: James Z. Wang, Jia Li and Gio Wiederhold,
 #      "SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture Libraries",
 #      IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 23, no. 9, pp. 947-963, 2001.
 #
-#   fuzzy
+#   fuzzy (unstable and unbalanced parameters)
 #      based on: Yixin Chen and James Z. Wang,
 #      "A Region-Based Fuzzy Feature Matching Approach to Content-Based Image Retrieval",
 #      IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 9, pp. 1252-1267, 2002.
@@ -48,14 +75,17 @@ TexturedThreshold   0.32
 #
 CompareMethod          integrated
 
-# Array of multiplicative constants in feature vectors distance computation
+# Array of multiplicative constants in feature vector distance computation
 # (L, u, v, LH, HL, HH, I1, I2, I3, X, Y). Each one must be an integer in range 0..15, default is 4.
 CompareFeaturesWeights 4 6 6 4 4 4 4 4 4 4 4
 
 }
 
-######## Duplicates finder ######################################################
+#endif
+#ifdef CONFIG_IMAGES_DUP
+######## Duplicate finder #######################################################
 
 ImageDup {
+# Detection of image duplicates does not work yet.
 }
-
+#endif