[[abstract]]車輛追蹤系統之自動化必須要克服的條件 非常眾多,本文提出新的辨認參數即是色彩,其 中包括有R(紅)、G(綠)、B(藍)以及(R-B)之影響,建 立了一不相似性指標做為計算辨認之門檻,另 外本文也提出多邊形視窗法以及Subostu三值法 解決實際影像的複雜度,由於多目標物體追蹤 尚是努力的領域,本文在二又二分之一D的側向 偵測的試驗中有較佳之效果。[[abstract]]An automatic vehicle tracking system has many important elements including preprocessing, detection, segmentation, features catching and targets recognition. This article adopts color features as the parameters of recognition and builds a dissimilarity index (D.I.) with the value of red (R), green (G), blue (B) and red minus blue (R-B). We try to use heuristic value(1200) as the threshold of recognition. Another we also try to establish two new segmentation processes, polygon window method and sub-ostu segmentation method, and we successfully segment the vehicle images. The study has 92. 41% recognition rate, on 2+(1/2)D condition.[[sponsorship]]大葉工學院; 行政院科技顧問組; 行政院產業自動化執行小組[[notice]]補正完畢[[conferencetype]]國內[[conferencedate]]19930703~19930703[[booktype]]紙本[[iscallforpapers]]Y[[conferencelocation]]臺中, 臺
