---

Face plays an important role in visual communication. By looking at the face, it can be automatically extracted many non-verbal messages, such as identity, intention, and emotion. In computer vision, localization of the key points of the face is usually a key step for automatic extraction of face information, and many facial analysis techniques are built on the precise recognition of these embossed. Facial landmark detection and alignment in images with occlusion is a very important and challenging task in many visual and image processing tasks. In this paper, a comprehensive method for initialization and alignment of facial landmark through training of local binary features (LBP) and histogram orientated gradient (HOG) and a facial landmark detection method using robust cascade pose regression, which are specified as pixel difference features of landmarks, is introduced. At first, by analyzing the correlation of the local binary pattern histogram (LBP) and then by using histogram orientated gradient, the features of the training images are obtained. For the test image using these features the instructional images are estimated as optimal guide points. In the test stage, according to initialization of the image, the selection of the appropriate feature for the image is used to speed up the process, which means the number of steps to be chosen for each image is better. A strong cascade mode regression is then used to adjust the face, and a local principle is applied to learn the features of the guide points. The local principle helps to learn a set of highly distinctive binary features for the face guide points independently; these local binary features are used to jointly learn the cascade mode regression for the final output. The results show that the initialization used in this work has increased the accuracy of the estimation in the cascade state regression and has obtained better results than the random initialization.

---

The same size of the helix steps in a traveling wave tube has a direct relationship with the efficiency of the system. In this article, the goal is to build a device that measures helix steps automatically and with proper accuracy by using image processing. For this purpose, the proposed algorithm was presented along with innovations in the fields of noise removal and threshold determination for the automatic measurement of helix steps, and the prototype of the device was made. This device has the ability to work in two modes of manual and automatic measurement, and it has no domestic equivalent, and it is much cheaper in terms of cost and use in measuring helix steps than the sample made abroad. In automatic mode, this device is able to measure all helix steps at once. In the case of a similar sample made abroad the steps must be measured manually and separately. The selection of the beginning and end points of steps in this device is done adaptively, which increases the speed of measurement and increases the repeatability in measuring steps. In the sample made abroad, the selection of the start and end points of the steps is done by the user, which reduces the repeatability of the measurement. The obtained results show that the measurement accuracy of the manufactured device is acceptable compared to the sample made abroad.