本篇論文提供一套產生鉛筆素描草圖的自動化流程，讓使用者無須介入而自動由 影像產生出近似手繪的草圖。然而，目前筆觸是完全由直線所構成，且長度是以圖像 的長寬為基礎，對於畫面複雜的圖來說，許多小細節會顯得十分雜亂；而對於顏色對 比過大的圖，畫面色階的分層會過於零碎，使的斜筆筆觸顯得十分不自然；Sobel 由 於 kernel 過小，有許多點的向量計算不出來，如何設計一個更大的且精準的 kernel 也可以是個議題；而筆跡與力道這方面的因素在本論文比較少著墨，這是未來可以加 以改進探討的地方。
在效能方面，ETF 及 FDoG 隨著 kernel 大小的與迭代的增加，運算時間會大幅增 加，而 FDoG 在的邊緣偵測上，需要計算許多高斯濾波，需要相對較長的時間。Kang[30]
等人在 ETF 提出以兩個 1D kernel 取代 2D kernel 來降低時間而達到近似的效果，
並也說到 FDoG 的實作上，以先計算出整個梯度強度圖來降低時間複雜度。而在本論 文中的筆觸生成方法，在實作上可以在輪廓擷取時就將三種長度筆觸同時處理；在 斜線筆觸方面，兩邊方向的也可以同時處理，以降低向量走訪次數，增加效能。
本論文從人工手繪的角度切入，彷彿就像一個畫家正著手對某張影像繪製素描，
也因此讓影像更能從擬真進入到非擬真，結果也顯示在素描草圖的模擬是很成功的。
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