Abstract: A substrate processing method includes performing a post-processing on a substrate subjected to a pre-processing, in the multiple chambers, acquiring a characteristic value of the substrate after the post-processing for respective chambers, calculating an actual value being an estimated value of the characteristic value when a processing condition of the post-processing is adjusted such that a difference between the characteristic value and a target value becomes small, acquiring a correction residual amount being a difference between the actual value and the target value for each chamber, calculating an average value of correction residual amounts of all of the chambers, correcting the pre-processing condition based on the average of the correction residual amounts, correcting the post-processing condition for each chamber based on the average of the correction residual amounts and the correction residual amount for each chamber; and performing the pre-processing and the post-processing based on the correcte

Abstract: An etching processing system includes a memory, and a processor coupled to the memory and configured to predict etching quality of a substrate by inputting image data of the substrate into a trained model trained by using training data in which image data of substrates captured by an imaging device arranged on a transfer path of the substrates and information for predicting etching quality of the substrates are associated with each other.

Abstract: A substrate processing apparatus includes a process module that includes: a stage having a first surface on which a substrate is placed and a second surface, a process module including an edge ring placed on the second surface, a measurement unit measuring an etching rate of the substrate; and a controller. The controller transfers the substrate to different transfer positions on the first surface and etches the substrate for each transfer position, acquires etching rates at points on a concentric circle of the substrate in an end of the substrate, for each transfer position, from the measurement unit, generates an approximate curve of each of the concentric circles based on each of the acquired etching rates for each transfer position, calculates each linear expression representing a movement direction of the substrate, based on the approximate curve for each transport position, and calculates an intersection coordinate of the linear expressions.

Abstract: An image processing apparatus includes a hardware processor configured to function as: a first generation unit that, from a first frame image and a second frame image in a past frame immediately successive to the first frame image, generates a first motion map showing a presence region of a moving object; a second generation unit that generates a moving object passage map showing a moving object passage region, by subtracting the first motion map from a past map image showing a presence region of the moving object included in a past frame image; a third generation unit that generates a second motion map by integrating the first motion map and the moving object passage map multiplied by a first value; and an adjustment unit that, based on the second motion map, adjusts a parameter related to noise reduction processing of the first frame image and the second frame image.

Abstract: A substrate processing method includes performing a post-processing on a substrate subjected to a pre-processing, in the multiple chambers, acquiring a characteristic value of the substrate after the post-processing for respective chambers, calculating an actual value being an estimated value of the characteristic value when a processing condition of the post-processing is adjusted such that a difference between the characteristic value and a target value becomes small, acquiring a correction residual amount being a difference between the actual value and the target value for each chamber, calculating an average value of correction residual amounts of all of the chambers, correcting the pre-processing condition based on the average of the correction residual amounts, correcting the post-processing condition for each chamber based on the average of the correction residual amounts and the correction residual amount for each chamber; and performing the pre-processing and the post-processing based on the correcte

Abstract: An imaging apparatus according to this invention comprises: an image capturing unit which performs continuous image capturing; a storing unit which stores a plurality of first images captured by the image capturing unit before a shutter button is pushed, and a plurality of second images captured by the image capturing unit after the shutter button is pushed; and a generating unit which generates a background image which is an image of a background of a dynamic body included in the first images and second images based on at least the plurality of first images.

Abstract: The present invention provides an imaging apparatus, an imaging method and a computer program which can automatically select an imaging method matching a scene and capture higher quality images. The imaging apparatus analyzes a preview image acquired from the image sensor before a shutter button is operated to classify the scene on which the preview image is obtained and, when the scene classified by the scene classifying unit is a night scene including a night view, controls the image sensor to continuously capture a plurality of images when the shutter button is operated.

Abstract: An imaging apparatus according to this invention comprises: an image capturing unit which performs continuous image capturing; a storing unit which stores a plurality of first images captured by the image capturing unit before a shutter button is pushed, and a plurality of second images captured by the image capturing unit after the shutter button is pushed; and a generating unit which generates a background image which is an image of a background of a dynamic body included in the first images and second images based on at least the plurality of first images.

Abstract: To enhance accuracy in correction of a defective pixel. An image of an object is captured using a digital camera, and stored in an image memory 14. A processor 16 detects a defect, using pixels located in the vertical and horizontal directions relative to, in lines of the same color as, and separated by one line from, the focused line. With any defect found, the presence or absence of line crawl is next determined. When it is determined that line crawl is present, the presence or absence of a diagonal edge is then determined. Subsequently, the surrounding pixels used to correct a defective pixel are selected in consideration of whether or not line crawl or a diagonal edge are present.

Abstract: A time to process an image signal used as a single frame image of a moving image. When an image signal used as a single frame image of a moving image is processed, a pixel value accumulated in a CCD element is read while being vertically and horizontally added with pixels (S30). The thus-read image signal is temporarily stored in internal memory after having undergone RGB color interpolation processing, resizing, YCC conversion processing, and the like, in a first image processing circuit that is a hardware circuit (S32, S34). A second image processing chip reads the image signal stored in the internal memory and expands the signal into a memory space. The image signal is subjected to comparatively-complicate image processing, including imperfect pixel correction processing, in the manner of software (S36). Since hardware processing and software processing are separated from each other, the number of memory expansion processing operations can be minimized, thereby shortening a processing time.

Abstract: To enhance accuracy in correction of a defective pixel. An image of an object is captured using a digital camera, and stored in an image memory 14. A processor 16 detects a defect, using pixels located in the vertical and horizontal directions relative to, in lines of the same color as, and separated by one line from, the focused line. With any defect found, the presence or absence of line crawl is next determined. When it is determined that line crawl is present, the presence or absence of a diagonal edge is then determined. Subsequently, the surrounding pixels used to correct a defective pixel are selected in consideration of whether or not line crawl or a diagonal edge are present.