Abstract: An optical imaging lens may include a first lens element, a second lens element, a third lens element, a fourth lens element, a fifth lens element and a sixth lens element positioned in an order from an object side to an image side. Through designing concave and/or convex surfaces of the lens elements and an inequality, the optical imaging lens may increase field of view, shrink volume and provide well image quality.

Abstract: A depth measurement apparatus including an illumination module, a beam splitter, an objective lens, an image capture module, a controller and a processor is provided. The illumination module is configured to generate an illumination beam. The beam splitter and the objective lens are disposed on an optical path of the illumination beam, and the object lens is configured to focus the illumination beam into a hole formed in an object. The image capture module is configured to capture images of the hole at different heights. The controller is coupled to the illumination module and the image capture module. The processor is coupled to the controller and the image capture module, and configured to perform focus distance evaluations on the images captured by the image capture module to obtain a height difference between two surfaces of the object. A depth measurement method is also provided.

Abstract: An image labeling apparatus, method, and computer program product are provided. The image labeling apparatus generates several image features of several to-be-processed images and classifies them into several groups. For each group, the image labeling apparatus: (a) selects the image feature closest to the center as a representative feature and a compared feature, (b) selects the image feature farthest to the compared feature as a candidate feature, and (c) compares the similarity between the candidate feature and each representative feature with a threshold. When all the similarities are smaller than the threshold, adopts the candidate feature as another representative feature and the compared feature and repeats (b) and (c). The group(s) whose number of representative features is more than another threshold will be re-classified.

Abstract: An image labeling apparatus, method, and computer program product are provided. The image labeling apparatus generates several image features of several to-be-processed images and classifies them into several groups. For each group, the image labeling apparatus: (a) selects the image feature closest to the center as a representative feature and a compared feature, (b) selects the image feature farthest to the compared feature as a candidate feature, and (c) compares the similarity between the candidate feature and each representative feature with a threshold. When all the similarities are smaller than the threshold, adopts the candidate feature as another representative feature and the compared feature and repeats (b) and (c). The group(s) whose number of representative features is more than another threshold will be re-classified.