CAJ | 학술논문

：为实现苹果目标的识别及其空间定位，提出了一种自然场景下苹果目标的识别与定位方法。该方法首先将 RGB 颜色空间转换至 HIS 颜色空间以得到自然场景下苹果图像的色调分量 H 和饱和度分量 S，为了充分利用其色调信息，采用了基于超红图像的苹果目标识别方法并应用基于区域的分割方法实现了目标的有效分割；接着利用轮廓曲率法抽取连续光滑的轮廓曲线并估计该光滑曲线段的圆心及其半径参数，实现果实的定位；最后利用逐行扫描法，结合苹果生理特性，实现了苹果采摘点的有效定位。为了验证算法的有效性，利用50幅富士苹果图像进行了试验。试验结果表明，苹果及其果柄的识别率在80%以上，对于轻度遮挡的苹果目标，基本满足其定位要求。
：위실현평과목표적식별급기공간정위，제출료일충자연장경하평과목표적식별여정위방법。해방법수선장 RGB 안색공간전환지 HIS 안색공간이득도자연장경하평과도상적색조분량 H 화포화도분량 S，위료충분이용기색조신식，채용료기우초홍도상적평과목표식별방법병응용기우구역적분할방법실현료목표적유효분할；접착이용륜곽곡솔법추취련속광활적륜곽곡선병고계해광활곡선단적원심급기반경삼수，실현과실적정위；최후이용축행소묘법，결합평과생리특성，실현료평과채적점적유효정위。위료험증산법적유효성，이용50폭부사평과도상진행료시험。시험결과표명，평과급기과병적식별솔재80%이상，대우경도차당적평과목표，기본만족기정위요구。
Aiming at realizing the recognition and localization of apples, a suitable algorithm that could be used in nature scene was proposed. On the first stage, the image was transformed from RGB color space to HIS color space, and the hue component H and the saturation component were got. To make full use of the hue information, a super-red theory was applied to segment apples. And then, the apple regions were got by combining region-based segmentation and mathematical morphology theory. After that, smooth contours were extracted by using contour curvature method and the center and radius parameters were estimated, which were essential for the localization of apples. On the final stage, apple picking points localization were realized by using progressive scanning method combined with apples’ physiological characteristics. To validate the algorithm, the experiments were carried out by using 50 Fuji apples. The results illustrated that the recognition rate of the apple and its stalk was above 80%. And the method proved to be feasi-ble and effective for slightly occluded apples.