restitution automation

RESTITUTION AUTOMATION FOR CLOSE-RANGE APPLICATIONS

Artemis Valanis, Andreas Georgopoulos

School of Rural and Surveying EngineeringLaboratory of Photogrammetry

National Technical University of Athens

Development of a semi- or fully- automated method for the restitution process of image products in the case of close-range applications

Applicability of the method for the case of Byzantine monuments

Trial applications on other kinds of monuments

OBJECTIVES

Construction complexity

Presence of decorative elements

Tuffstone is the basic construction material

OBJECT DESCRIPTION

Extensive research of the properties of the object of interest and trial application of several image processing techniques

Development of a method for the detection of the objects of interest

Program and interface development

Application of the proposed method for Byzantine and other kinds of monuments

Evaluation of the results

COURSE OF STUDY

Noise reduction methods (mean-, order statistics and adaptive filters)

Image enhancement in the frequency domain (FFT, Ideal filters, Butterworth filters)

Edge detection algorithms (Sobel, Prewitt, Canny, LoG, color edge detection)

Morphological processing (erosion, dilation, morphological gradient)

Segmentation and thresholding techniques

TRIAL APPLICATIONS OF VARIOUS IMAGE PROCESSING TECHNIQUES

Object complexityStrong resemblance in the appearance of the stones and jointsExistence of inclinated planes and shadowed areasErosion of the construction material Presence of moisture

PROBLEMS ENCOUNTERED IN THE DETECTION OF THE OBJECTS

Sample selectionCalculation of the mean value and standard deviation of the gray values of the pixels of the sample Region Growing

PROPOSED APPROACH

ROUTE FOLLOWED BY THE ALGORITHM

REGIONS EXAMINED BY THE ALGORITHM ACCORDING TO THE POSITION OF THE CANDIDATE PIXEL

• Connectivity criterion: At least two pixels of the examined region must belong to the object

• Homogeneity criterion: The arithmetic (mr) mean of the gray values of the candidate and the identified as object pixels of the currently examined region must belong in the confidence interval given by Equation [1]

ms - z ss mr ms + z ss [1]

CRITERIA EVALUATED BY THE ALGORITHM

DETECTION RESULTS FOR A SINGLE OBJECT

Definition of the area to be processed Sample selection for the objects that must be detected Application of an adaptive thresholding technique Improvement of the binary image which is yielded by the

thresholding process Exploitation of the improved binary image for the

automated sample selection Application of the algorithm for each one of the objects

detected

AUTOMATION OF THE PROCESS

EXAMPLE

INTERFACE OF THE PROGRAM

APPLICATIONS – BYZANTINE MONUMENTS

EXPERIMENTS FOR THE CASE OF THE DOME

EXPERIMENTS FOR THE DECORATIVE ELEMENTS

FINAL RESULTS AND COMPARISON

Tolerance: σTolerance: 2σTolerance: 3σ

EVALUATION

EVALUATION

Distance from

manually collected

boundaries(mm)

Sample 1(11559 pixels)

Sample 2(8485 pixels)

Total(20044 pixels)

Pixels percentage pixels percentage pixels percentage

d σ 8020 69% 5371 63% 13391 67%

2σ d 2σ 2251 20% 1909 23% 4160 21%

3σ d 3σ 740 6% 747 9% 1487 7%

d> 3σ 548 5% 458 5% 1006 5%

The proposed method is very flexible and fast

The program used for the application of the developed methods offers a wide range of possibilities and is user friendly

The accuracy of the restitution is objectively characterized as satisfactory for the case of Byzantine monuments

The restitution process is accelerated by a factor of at least 1.7

CONCLUSIONS

Examination of more complex properties such as texture Thorough review and further development of the fully

automated method Detailed research of the properties of other kinds of

monuments

SUGGESTIONS

Thank you for your attention!

VECTORIZATION

ARCH OF ADRIANOS

NATIONAL THEATRE

Distance from

manually collected

boundaries(mm)

Sample 1(11122 pixels)

Sample 2(9067 pixels)

Pixels percentage pixels percentage

d σ 7859 70% 5371 28%

2σ d 2σ 1934 18% 1909 22%

3σ d 3σ 382 3% 747 18%

d> 3σ 947 9% 458 32%

BYZANTINE WALL (DAPHNI MONASTERY)