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1.	Sladoje, Natasa, et al. (författare) Distance Between Vector-Valued Representations of Objects in Images with Application in Object Detection and Classification 2017 Ingår i: In Proc. of the 18th International Workshop on Combinatorial Image Analysis, IWCIA2017. - Cham : Springer. - 9783319591070 - 9783319591087 ; , s. 243-255 Konferensbidrag (refereegranskat)abstract We present a novel approach to measuring distances between objects in images, suitable for information-rich object representations which simultaneously capture several properties in each image pixel. Multiple spatial fuzzy sets on the image domain, unified in a vector-valued fuzzy set, are used to model such representations. Distance between such sets is based on a novel point-to-set distance suitable for vector-valued fuzzy representations. The proposed set distance may be applied in, e.g., template matching and object classification, with an advantage that a number of object features are simultaneously considered. The distance measure is of linear time complexity w.r.t. the number of pixels in the image. We evaluate the performance of the proposed measure in template matching in presence of noise, as well as in object detection and classification in low resolution Transmission Electron Microscopy images.

Sladoje, Natasa, et al. (författare)
Distance Between Vector-Valued Representations of Objects in Images with Application in Object Detection and Classification
2017
Ingår i: In Proc. of the 18th International Workshop on Combinatorial Image Analysis, IWCIA2017. - Cham : Springer. - 9783319591070 - 9783319591087 ; , s. 243-255
Konferensbidrag (refereegranskat)abstract
- We present a novel approach to measuring distances between objects in images, suitable for information-rich object representations which simultaneously capture several properties in each image pixel. Multiple spatial fuzzy sets on the image domain, unified in a vector-valued fuzzy set, are used to model such representations. Distance between such sets is based on a novel point-to-set distance suitable for vector-valued fuzzy representations. The proposed set distance may be applied in, e.g., template matching and object classification, with an advantage that a number of object features are simultaneously considered. The distance measure is of linear time complexity w.r.t. the number of pixels in the image. We evaluate the performance of the proposed measure in template matching in presence of noise, as well as in object detection and classification in low resolution Transmission Electron Microscopy images.

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