为了通过目标区域内弦的分布稳定地描述目标的形状特征，首先定义了区域主弦和基于主弦的垂直扫描弦。并由区域主弦和垂直扫描弦的长度、位置分布组成了目标区域弦分布；然后根据区域弦分布，定义了区域弦面积、弦平行度、边界点对称率、主弦长度、弦方框率等描述目标区域形状的有效特征；最后利用区域弦分布形状描述特征对一些简单形状和显微镜细胞图像进行了实验。实验结果表明，区域弦分布形状特征不仅可以有效区分圆、椭圆、矩形、平行四边形和不规则多边形等简单形状，而且在显微镜细胞自动分类与识别系统中增加细胞区域弦分布特征后，目标识别率明显提高,误判率明显降低。另外，通过弦分布形状特征，系统还可以有效区分长条管形细胞、方形结晶细胞、圆形细胞和不规整细胞的形状。

In order to describe the object’s shapes steadily by chordal distribution in object’s region, region main chord and it’s perpendicular scanning chords were defined firstly in the paper and their computation method was put forward. Object region chordal distribution is composed of main chord and perpendicular scanning chords. According to main chord and perpendicular scanning chords length and position, the paper defined such effective shape features as chordal area, parallelism degree, edge points symmetry proportion, main chord length and chordal square rate. Finally, the paper used these region chordal features dealing with some simple shapes and cell images.The result showed that these features can distinguish round, ellipse, rectangle, parallelogram and anomalistic polygon. At the same time the cell identifying ratio was improved and misjudgment ratio depressed obviously after the cell region’s chordal features were used in microscopical cell image classifying and recognition system.The system distinguished the shapes among strip tube cell and quadrate rime and round cell and anomalous epithelia effectively.