The main aim of our work is to develop the new R package curde. The package is used to detect line or conic curves in a digital image. The package contains the Hough transformation for a line detection using the accumulator. The Hough transform is a feature extraction technique and its purpose is to find imperfect instances of objects within a certain class of shapes. This technique is not suitable for curves with more than three parameters. For conic fitting, robust regression is used. For noisy data, solution based on Least Median of Squares (LMedS) is highly recommended. In this package, algorithms for non-user image evaluation is implemented. The whole process of the non-user image evaluation includes the image preparation. The preparation consists of various methods such as image grayscaling, thresholding or histogram estimation. The conversion from the grayscaled image to binary is realised by the calculation of the Sobel operator convolution and by the application of the threshold technique. After that the convolution technique is applied. The new R package curde will be the integration of all previous techniques to the one complex package.