Segmentation of Sea-bed Images.

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Presentation transcript:

Segmentation of Sea-bed Images. Josepha UNIA Ecole Centrale de Lyon 21 / 06 / 2000 Segmentation of Sea-bed Images.

Segmentation of Sea-bed Images. Summary Introduction Sensing Image segmentation Vector quantization Preliminary results Perspectives 21 / 06 / 2000 Segmentation of Sea-bed Images.

Segmentation of Sea-bed Images. Introduction Marine application : Mapping of living/dead Maerl. Provide the information necessary for a safe and sustainable exploitation of underwater resources. Develop and implement mathematical models, and sensing and guidance techniques 21 / 06 / 2000 Segmentation of Sea-bed Images.

Segmentation of Sea-bed Images. Sensing (WP3, subtask 3.1) Design signal processing algorithms for : on-line extraction of features for platform guidance Segmentation of video images video mosaicing using contour information to correct (effects of) positioning errors 21 / 06 / 2000 Segmentation of Sea-bed Images.

Segmentation of Sea-bed Images. Image segmentation Segmentation Contour-extraction Image ROV Control 21 / 06 / 2000 Segmentation of Sea-bed Images.

Segmentation of Sea-bed Images. Vector quantization Dictionary What size for dictionary ? What words ? What size for window (vector) ? What resemblance measure ? 21 / 06 / 2000 Segmentation of Sea-bed Images.

Segmentation of Sea-bed Images. Algorithm Outline Dictionary learning Initialize dictionary (centroid of all vectors - windows) Split until desired dictionary size is reached PARTITIONING : make best attribution of each vector to current dictionary CORRECT DICTIONARY to get minimal distortion (for current partioning) 21 / 06 / 2000 Segmentation of Sea-bed Images.

Preliminary results (1) Dic 2 4 16 32 Window 3 x 3 10 x 10 30 x 30 21 / 06 / 2000 Segmentation of Sea-bed Images.

Preliminary results (2) Frame 01 Frame 02 Frame 03 Frame 04 2 CODEWORDS - WINDOW 10x10 F_out 01 F_out 02 F_out 03 F_out 04 21 / 06 / 2000 Segmentation of Sea-bed Images.

Preliminary results (3) Frame 01 Frame 02 Frame 03 Frame 04 16 CODEWORDS - WINDOW 10x10 F_out 01 F_out 02 F_out 03 F_out 04 21 / 06 / 2000 Segmentation of Sea-bed Images.

Lower resolution image What resolution ? Window 10x10 & 2 clusters 21 / 06 / 2000 Segmentation of Sea-bed Images.

Segmentation of Sea-bed Images. Perspectives Learning representation of classes (coverage with enough vectors) rotation invariance Choice of distance Euclidean distance good for compression Distance more sensitive to texture variation Automatic tuning of the algorithm’s parameters distance size of windows size of dictionary. Adaptive adjustment (tracking of classes’ characteristics) 21 / 06 / 2000 Segmentation of Sea-bed Images.