Analysis of Application of Cluster Descriptions in Space of Characteristic Image Features
Abstract: Structural image recognition method modifications in space of characteristic features for recognition of computer vision image dataset were investigated. Recognition performance boost is achieved with quantization (clustering) in the space of image characteristic features that form the pattern of the object. Due to the transformation of structural objects descriptions from a set representation to a vector form, the amount of computation might be reduced tens of times. The results of experiments on Leeds Butterfly dataset that confirmed the effectiveness of decision-making systems based on the proposed approach are shown.
computer vision, structural recognition methods, set of characteristic features, descriptor, quantization, competitive learning
Gorokhovatskyi O. Analysis of Application of Cluster Descriptions in Space of Characteristic Image Features / O. Gorokhovatskyi, V. Gorokhovatskyi, O.Peredrii // Data. – 2018, 3(4), 52. – doi:10.3390/data3040052. Available online: https://www.mdpi.com/2306-5729/3/4/52