Abstract: A 3D image mask analysis method is applied to an image surveillance apparatus having an image receiver and an operation processor. The 3D image mask analysis method includes establishing a 3D image mask with first depth information inside a surveillance image acquired by the image receiver, utilizing an object identification technology to acquire second depth information of a target object at least partly overlapped with the 3D image mask inside the surveillance image, and comparing the first depth information to the second depth information so as to determine whether an image of the target object is displayed inside the surveillance image in accordance with a comparison result.

Abstract: A sheltering mechanism applied to a surveillance camera and includes a sheltering component and a resilient component. The casing includes an opening. The sheltering component is slidably disposed on a casing to shelter an opening formed on the casing. The opening is surrounded by the resilient component. The resilient component includes a base portion, a bridging portion and a contacting portion. The base is fixed to the casing. The bridging component is connected to the base portion and stretches outwardly from the base portion. The contacting portion is disposed on an end of the bridging portion opposite to the base portion. The bridging portion pushes the contacting portion to contact against the sheltering component for sealing a gap between the casing and the sheltering component.

Abstract: A tension adjustment mechanism applied to a surveillance camera and includes a base, a positioning component, a first actuating component and a first fixing component. The base includes a first slot and first hole. The positioning component is slidably disposed on the base. The first actuating component has a first fixed end and a first free end opposite to each other. The first fixed end is fixedly disposed on the positioning component. The first free end has an inclined guiding structure and is movably inserted into the first slot. The first fixing component abuts against the inclined guiding structure and is movably locked with the first hole.

Abstract: An object sampling method is applied to an image analysis apparatus with an image receiver and an operation processor. The image receiver acquires an image stream. The object sampling method includes transforming color space of at least one surveillance image in the image stream, computing saturation and gradient of specific pixels within the at least one surveillance image, setting a bonding box within the at least one surveillance image, and computing a background score relevant to the saturation and value of all pixels in the bonding box, and comparing the background score with a first sampling condition so as to determine whether the at least one surveillance image is applicable for the image analysis apparatus via a comparison result of comparing the foreground score with the first sampling condition.

Abstract: An image analysis model adjustment method is applied to an image analysis apparatus. The image analysis model adjustment method includes dividing a detection image acquired by the imager analysis apparatus into a plurality of first sub-images via a valid size, transforming the plurality of first sub-images from a spatial domain to a frequency domain to generate a plurality of first frequency domain images, distributing the plurality of first frequency domain images into several crop groups via a predefined set value, analyzing frequency responses at the same frequency in each crop group to provide a specific frequency response, collecting specific frequency responses of the crop groups to generate frequency domain group data, and analyzing the frequency domain group data to acquire a prediction result of the detection image so as to decide whether to adjust the valid size in accordance with the predicted result.

Abstract: An image information transformation method is applied to an image analysis device with an operation processor and includes generating a false object datum in a predefined manner, and deciding whether to output the false object datum in accordance with an identification result of a user license.

Abstract: An image analysis method is applied to a camera apparatus and used to analyze the landform inside a detection image captured by the camera apparatus via a predefined installation angle. The image analysis method includes dividing the detection image into a plurality of first regions to acquire a plurality of first height, defining some first regions with the same height and adjacent to each other as a first reference plane area to acquire a first plane formula, selecting at least one first region adjacent to and outside the first reference plane area, applying the selected first region for the first plane formula to acquire a first planar height and comparing the first planar height with an initial first height of the at least one first region, and determining landform between the first reference plane area and the selected at least one first region in accordance with a comparison result.

Abstract: An image defect identification method is applied to an image analysis device with an image receiver and an operation processor. The image defect identification method divides a detection image acquired by the image receiver into a plurality of pixel groups, transforms one of the plurality of pixel groups into a distribution curve, compares the distribution curve with a reference curve, and determines an area of the detection image conforming to a specific section of the distribution curve has defect when a difference between the specific section of the distribution curve and a related section of the reference curve is greater than a predefined threshold.

Abstract: An image calibration method applied to an image calibration device includes comparing a first image with a second image to acquire a first overlapping region of the first image and a second overlapping region of the second image, analyzing color distribution of the first overlapping region to acquire at least one first base color value, analyzing color distribution of the second overlapping region to acquire at least one second base color value, setting a ratio of the at least one first base color value to the at least one second base color value as an luminance compensation value when the at least one first base color value is greater than the at least one second base color value, and utilizing the luminance compensation value to adjust pixels of the second image. The first overlapping region is overlapped with the second overlapping region.

Abstract: An object counting method is applied to a surveillance camera and used to determine an amount and a direction an object passing over a surveillance region. The object counting method includes acquiring a plurality of known traces, dividing the plurality of known traces into a first group passing the surveillance region along a first direction and a second group passing the surveillance region along a second direction, computing a first start point computed value of the first group and a second start point computed value of the second group to acquire a start point connection vector, and comparing the start point connection vector with a trace vector of a target object to determine whether the target object passes over the surveillance region along the first direction or the second direction.

Abstract: An image restoration method is applied to an image restoration device and includes acquiring an analyzing image containing a region of interest and a background region, utilizing a first restoration function to calibrate the region of interest and generate a calibrated region of interest, and combining the calibrated region of interest with the background region via a relative position between the region of interest and the background region for providing a restoration image.

Abstract: An automatic feeding device includes an accommodating container, a transmission channel, a valve unit, a sensor and an ejection unit. The transmission channel is disposed on bottom of the accommodating container. The transmission channel has an inlet portion, a central portion and an outlet portion. The central portion is between the inlet portion and the outlet portion. The valve unit is disposed on the bottom of the accommodating container and adjacent to the inlet portion. The valve unit is switchable to allow feed inside the accommodating container for passing the inlet portion and entering the transmission channel. The sensor is disposed on the inlet portion and detects whether the feed passes the inlet portion, and further outputs a control command to switch modes of the valve unit. The ejection unit is disposed on the central portion and used to push the feed inside the transmission channel toward the outlet portion.

Abstract: An image analysis model establishment method is applied to an image analysis apparatus including an imager receiver and an operation processor. The image analysis model establishment method divides a detection image acquired by the imager receiver into a plurality of sub-images and transforms the sub-images from a spatial domain to a frequency domain to generate a plurality of pre-processing frequency domain data, generating an analysis model output layer by an inner product of the plurality of pre-processing frequency domain data transformed via a plurality of masks and several filters through a fully connected multilayer perceptron network, acquiring a predicted result of the detection image in accordance with a category determination result of the analysis model output layer, and comparing the predicted result with a target label to adjust parameters in each transformation phase applied for the plurality of pre-processing frequency domain data in accordance with a comparison result.

Abstract: An object classifying and tracking method is applied to an image stream acquired by a surveillance camera for object identification. The object classifying and tracking method includes acquiring a first classify feature and a first dependent feature of a first target object in a first image of the image stream and a second classify feature and a second dependent feature of a second target object in a second image of the image stream, acquiring a dependent degree of the first classify feature and the second classify feature from a memory, transforming the second dependent feature via the dependent degree, and analyzing the first dependent feature and the transformed second dependent feature to determine whether the first target object and the second target object are the same object.

Abstract: A tension adjustment mechanism applied to a surveillance camera and includes a base, a positioning component, a first actuating component and a first fixing component. The base includes a first slot and first hole. The positioning component is slidably disposed on the base. The first actuating component has a first fixed end and a first free end opposite to each other. The first fixed end is fixedly disposed on the positioning component. The first free end has an inclined guiding structure and is movably inserted into the first slot. The first fixing component abuts against the inclined guiding structure and is movably locked with the first hole.