Tanahashi Masahiko, Lin Min-Chen, Lin Chung-Ping
Institute of Plant and Microbial Biology, Academia Sinica, Taipei, Taiwan.
Department of Life Science, National Taiwan Normal University, Taipei, Taiwan.
PLoS One. 2025 Jul 22;20(7):e0300238. doi: 10.1371/journal.pone.0300238. eCollection 2025.
Disruptive colorations are camouflaging patterns that use contrasting colorations to interrupt the continuity of object's edge and disturb the observer's visual recognition. The GabRat method has been introduced and widely used to quantify the strength of edge disruption. The original GabRat method requires a composite image where a target object is placed on a particular background. It computes the intensities of 'frequency components' parallel and perpendicular to the edge direction at each edge point using Gabor filters, and summarizes the ratios of these two intensities around the perimeter of the shape. However, we found that the original GabRat method has an issue that produces false signals and biases to overestimating the GabRat value depending on the edge angle. Here, we introduce GabRat-R, which can diminish that angle dependency using Gabor filters with randomized base angles. Additionally, we developed GabRat-RR, which iteratively places a target object on a background with random positions and rotation angles to average the effects of the heterogeneity and anisotropy of background. Compared with the original GabRat, our GabRat-R and GabRat-RR programs run more efficiently using multithreading techniques. Those programs are provided as built-in features of the Natsumushi 2.0 software and available from the GitHub repository, https://github.com/mtlucanid/GabRat-R.
破坏性色彩是一种伪装图案，它利用对比色来中断物体边缘的连续性，并干扰观察者的视觉识别。GabRat方法已被引入并广泛用于量化边缘破坏的强度。原始的GabRat方法需要一个合成图像，其中目标物体放置在特定背景上。它使用Gabor滤波器计算每个边缘点处平行和垂直于边缘方向的“频率分量”强度，并汇总形状周边这两种强度的比率。然而，我们发现原始的GabRat方法存在一个问题，即根据边缘角度会产生虚假信号并导致偏向高估GabRat值。在此，我们引入GabRat-R，它可以使用具有随机基角的Gabor滤波器来减少角度依赖性。此外，我们开发了GabRat-RR，它通过在具有随机位置和旋转角度的背景上迭代放置目标物体，以平均背景的异质性和各向异性的影响。与原始的GabRat相比，我们的GabRat-R和GabRat-RR程序使用多线程技术运行得更高效。这些程序作为Natsumushi 2.0软件的内置功能提供，可从GitHub存储库https://github.com/mtlucanid/GabRat-R获取。
