A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Iterative Tuning of Simple Cells for Contrast Invariant Edge Enhancement
BMCV '02 Proceedings of the Second International Workshop on Biologically Motivated Computer Vision
Extracting Multispectral Edges in Satellite Images over Agricultural Fields
ICIAP '99 Proceedings of the 10th International Conference on Image Analysis and Processing
Bio-Inspired Artificial Intelligence: Theories, Methods, and Technologies
Bio-Inspired Artificial Intelligence: Theories, Methods, and Technologies
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Robot's vision plays a significant role in human-robot interaction, e.g., face recognition, expression understanding, motion tracking, etc. Building a strong vision system for the robot, therefore, is one of the fundamental issues behind the success of such an interaction. Edge detection, which is known as the basic units for measuring the strength of any vision system, has recently been taken attention from many groups of robotic researchers. Most of the reported works surrounding this issue have been based on designing a static mask, which sequentially move through the pixels in the image to extract edges. Despite the success of these works, such statically could restrict the model's performance in some domains. Designing a dynamic mask by the inspiration from the basic principle of "retina", and which supported by a unique distribution of photoreceptor, therefore, could overcome this problem. A human-like robot (RobovieR-2) has been used to examine the validity of the proposed model. The experimental results show the validity of the model, and it is ability to offer a number of advantages to the robot, such as: accurate edge detection and better attention to the front user, which is a step towards human-robot interaction.