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git-svn-id: https://tesseract-ocr.googlecode.com/svn/trunk@289 d0cd1f9f-072b-0410-8dd7-cf729c803f20
81 lines
3.4 KiB
C++
81 lines
3.4 KiB
C++
///////////////////////////////////////////////////////////////////////
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// File: detlinefit.h
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// Description: Deterministic least upper-quartile squares line fitting.
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// Author: Ray Smith
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// Created: Thu Feb 28 14:35:01 PDT 2008
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//
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// (C) Copyright 2008, Google Inc.
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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// http://www.apache.org/licenses/LICENSE-2.0
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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//
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///////////////////////////////////////////////////////////////////////
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#ifndef TESSERACT_CCSTRUCT_DETLINEFIT_H_
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#define TESSERACT_CCSTRUCT_DETLINEFIT_H_
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#include "points.h"
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namespace tesseract {
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// This class fits a line to a set of ICOORD points.
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// There is no restriction on the direction of the line, as it
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// uses a vector method, ie no concern over infinite gradients.
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// The fitted line has the least upper quartile of squares of perpendicular
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// distances of all source points from the line, subject to the constraint
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// that the line is made from one of the pairs of [{p1,p2,p3},{pn-2, pn-1, pn}]
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// i.e. the 9 combinations of one of the first 3 and last 3 points.
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// A fundamental assumption of this algorithm is that one of the first 3 and
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// one of the last 3 points are near the best line fit.
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// The points must be Added in line order for the algorithm to work properly.
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// No floating point calculations are needed* to make an accurate fit,
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// and no random numbers are needed** so the algorithm is deterministic,
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// architecture-stable, and compiler-stable as well as stable to minor
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// changes in the input.
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// *A single floating point division is used to compute each line's distance.
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// This is unlikely to result in choice of a different line, but if it does,
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// it would be easy to replace with a 64 bit integer calculation.
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// **Random numbers are used in the nth_item function, but the worst
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// non-determinism that can result is picking a different result among equals,
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// and that wouldn't make any difference to the end-result distance, so the
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// randomness does not affect the determinism of the algorithm. The random
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// numbers are only there to guarantee average linear time.
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// Fitting time is linear, but with a high constant, as it tries 9 different
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// lines and computes the distance of all points each time.
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// This class is aimed at replacing the LLSQ (linear least squares) and
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// LMS (least median of squares) classes that are currently used for most
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// of the line fitting in Tesseract.
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class DetLineFit {
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public:
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DetLineFit();
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~DetLineFit();
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// Delete all Added points.
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void Clear();
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// Add a new point. Takes a copy - the pt doesn't need to stay in scope.
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// Add must be called on points in sequence along the line.
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void Add(const ICOORD& pt);
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// Fit a line to the points, returning the fitted line as a pair of
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// points, and the upper quartile error.
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double Fit(ICOORD* pt1, ICOORD* pt2);
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private:
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double ComputeErrors(const ICOORD start, const ICOORD end, int* distances);
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ICOORDELT_LIST pt_list_; // All the added points.
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};
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} // namespace tesseract.
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#endif // TESSERACT_CCSTRUCT_DETLINEFIT_H_
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