本文選題：輪廓檢測　切入點(diǎn)：顏色拮抗　出處：《中國生物醫(yī)學(xué)工程學(xué)報》2017年05期 　論文類型：期刊論文

【摘要】：基于神經(jīng)元的顏色拮抗特性及神經(jīng)元群體的動態(tài)編碼機(jī)制,實(shí)現(xiàn)對圖像的輪廓檢測。模擬視皮層下神經(jīng)元的顏色單拮抗特性,引入單拮抗感受野的動態(tài)調(diào)節(jié)機(jī)制,以充分響應(yīng)顏色邊界和亮度邊界;利用單細(xì)胞的樹突極性分布,構(gòu)建初級視皮層的雙拮抗神經(jīng)元網(wǎng)絡(luò),實(shí)現(xiàn)對特定方位的視覺刺激響應(yīng),有效提取目標(biāo)輪廓;在神經(jīng)元的群體感受野內(nèi),考慮神經(jīng)元的動態(tài)突觸連接,融合單細(xì)胞的脈沖頻率響應(yīng),實(shí)現(xiàn)對紋理信息的抑制作用。以BSDS500圖庫的圖像為實(shí)驗(yàn)對象,結(jié)果顯示該方法在提取主體輪廓的過程中能有效抑制紋理信息,其對100幅圖像最佳檢測結(jié)果的P值指標(biāo)均值和標(biāo)準(zhǔn)差為0.58±0.04,相對CORF和CO等其他對比方法,可提高輪廓提取的準(zhǔn)確率。所提出方法可有效實(shí)現(xiàn)圖像的輪廓檢測,為利用顏色信息以及神經(jīng)元之間的動態(tài)編碼、實(shí)現(xiàn)更高級皮層的圖像理解或者視覺認(rèn)知提供新的思路。
[Abstract]:Based on the color antagonistic characteristics of neurons and the dynamic coding mechanism of neuronal population, the contour detection of images is realized, and the dynamic regulation mechanism of single antagonistic receptive field is introduced to simulate the color single antagonistic characteristic of subcortical neurons. In order to fully respond to the color boundary and luminance boundary, the dual antagonistic neural network of primary visual cortex was constructed by using the dendritic polarity distribution of single cell, and the visual stimulation response to specific position was realized, and the contour of target was extracted effectively. In the population sensing field of neurons, the dynamic synaptic connection of neurons is considered, and the pulse frequency response of single cell is fused to suppress the texture information. The results show that this method can effectively suppress the texture information in the process of extracting the main contour. The average value and standard deviation of P value of the best detection results for 100 images are 0.58 鹵0.04, which are relative to other comparison methods, such as CORF and CO, etc. The proposed method can effectively realize contour detection of images and provide a new idea for image understanding or visual cognition of higher cortex by using color information and dynamic coding between neurons.
【作者單位】： 杭州電子科技大學(xué)模式識別與圖像處理實(shí)驗(yàn)室;
【基金】：國家自然科學(xué)基金(61501154)
【分類號】：R338;TP391.41

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1 周彥博,張志廣,楊福生;顯微圖像中可變形物體動態(tài)跟蹤方法的研究[J];中國生物醫(yī)學(xué)工程學(xué)報;1998年02期

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